This PDF file contains the front matter associated with SPIE Proceedings Volume 7127, including the Title Page, Copyright information, Table of Contents, and the Conference Committee listing.

A novel method for achieving high resolution for static strain measurement is proposed and demonstrated. This method is based on the combination of two fiber Bragg grating (FBG) and an all-fiber Fabry-Perot sensor (FFPI) formed by the two FBGs. The wavelength shift of the FBGs is used for determining the fringe number of the interferometic signal while the FFPI and the pseudo-heterodyne are used to carry out high-resolution measurement. The resolution for static strain by the actual measuring is 31nε.

Wireless sensor networks (WSN) have wide applicability to many important applications including environmental monitoring, military applications and disaster management, etc. In many applications, sensors are assumed to know their absolute locations. Some localization methods of WSN have been proposed. In these methods, nodes equipped with GPS to get precise location information, namely the anchor nodes, are employed to derive the locations of other nodes. Most of the recent work focuses on increasing the accuracy in position estimation. In this paper, aiming at the high communication cost and average positioning error of DV-hop algorithm, an advanced algorithm which is called ADV-hop algorithm is proposed. Simulations are made by the network simulator NS2. The simulation results show that ADV-hop algorithm has lower communication cost and smaller average positioning error than DV-hop algorithm, which makes ADV-hop algorithm more suitable for the node location of WSN.

This paper presents a measuring system of vibration acceleration for acoustic emission wave using wavelet signal reconstruction technology. Continuous wave modulation frequency and wavelength division multiplex technology are adopted to realize distributed sensing system demodulation. Double FBGs acceleration probe with compressive stress and tensile stress applying simultaneity is designed. In this way, the influence of temperature noise on sensing signals is eliminated and measurement sensitivity and resolution are enhanced. Using wavelet signal processing methods not only completed the optical wavelength absolute code, improve imbalanced and nonlinear optical signal efficiently, but also reconstruct micro accelerate signal. This system has some advantages such as simple structure, high scan frequency, high resolution and good linearity.

Laser polarimetric remote sensing has great potential in target detection, recognition and classification. Here, we propose a modified laser polarimetric active imaging system. Principles and advantages of polarimetric detection are discussed. Illuminating with a semiconductor laser, receiving by a Cassegrain telescope, splitting by a polarization beam splitter (PBS), two images are created on two CCDs simultaneously. Two images of orthogonal polarization states can be obtained once by using this system and then intensity and polarization degree can be calculated. Dual images coded with intensity and polarization degree of testing target are obtained and analyzed. Preliminary experiments are conducted, and the result shows the feasibility of the new method. Image coded with polarization degree can distinguish target, which cannot be realized in intensity image when the targets have similar reflectivity. Intensity image and polarization degree image can be fused together through HSI (Hue, Saturation and Intensity) pseudocolor coding. In the fusion image, different depolarization targets display in different colors, hence the purpose of classifying targets with same material can be achieved. Compared with traditional approaches which needing 16 images or 2 images, the new method has extremely improved the measurement efficiency and provides a new way for real-time polarimetric imaging.

With the rapid development of micro-computer technology, embedded system, CNC technology and integrated circuits, numerical control system with powerful functions can be realized by several high-speed CPU chips and RISC (Reduced Instruction Set Computing) chips which have small size and strong stability. In addition, the real-time operating system also makes the attainment of embedded system possible. Developing the NC system based on embedded technology can overcome some shortcomings of common PC-based CNC system, such as the waste of resources, low control precision, low frequency and low integration. This paper discusses a hardware platform of ENC (Embedded Numerical Control) system based on embedded processor chip ARM (Advanced RISC Machines)-S3C2410 and DSP (Digital Signal Processor)-MCX314AL and introduces the process of developing ENC system software. Finally write the MCX314AL's driver under the embedded Linux operating system. The embedded Linux operating system can deal with multitask well moreover satisfy the real-time and reliability of movement control. NC system has the advantages of best using resources and compact system with embedded technology. It provides a wealth of functions and superior performance with a lower cost. It can be sure that ENC is the direction of the future development.

In view of the current technical problems existing in multiphase flow metering, slotted orifice-couple flow meter was introduced and the basic principles for measurement were presented. A new wet gas flow meter is developed based on the dual slotted orifice. The flow characteristic of liquid flowing through dual slotted orifice plate, relationship of differential pressure between the dual slotted orifice plate, pressure, temperature, and flow rate of gas/liquid of different aperture ratio were studied. The mathematical measurement model applicable to the dual slotted orifice plate flow meter measurement system was established. The model was applied to onsite experiment and the calibration of China National Center of Metrology at Daqing Oil field. The results showed that the maximum measurement error of the gas phase flow was less than 10% and that of the liquid phase flow was less than 15%. The measurement accuracy of this industrial prototype can meet requirement of practical production.

Introduced the structure of a magnetic bearing reaction wheel for stabilization of spacecraft attitude, its rotation speed is from -5000rpm to 5000rpm (rating angular momentum is 20Nms). The main scope of this paper is to calculate and analyze the performance and parameters of the hybrid thrust magnetic bearing with permanent magnet bias for the magnetic bearing momentum wheel. Its magnetic force, current stiffness, and position stiffness are derived by using the equivalent magnetic circuit and their non-linearity are shown by the curves of force-current-position characteristic. The ranges of bearing capacity is obtained.

The paper presents one kind of digital remote image surveillance system based on application-embedded system, and offers the reference design of hardware using ARM processor and FPGA technology. Based on the system, practical digital remote surveillance system can be developed, which is suitable for the low-resolution, low-cost, and long-distance surveillance application using narrowband system based on public telephone network. At the same time, practical digital remote surveillance system can provide the high-quality images.

In view of the force-sensor used in the multi-support rotor-bearing test-bed and the calibration process of the force-sensor, this paper shows the force-sensor possesses good static and dynamic characteristics, the strain curve presents itself linear, and the degree of linearity of it is eligible after the linear regression of the in-put and out-put curves. This paper can be used in the calibration of other sensors with similar structures.

Capacitive micromachined ultrasonic transducers (CMUTs) have been developed for airborne ultrasonic applications, acoustic imaging, and chemical and biological detections. Much attention is also paid how to optimize their performance, so that the accurate simulation of the transmitting response of the CMUTs becomes extremely significant. This paper focuses on determining the total input mechanical impedance accountings for damping, and its resistance part is obtained by the calculated natural frequency and equivalent lumped parameters, and the typical 3-dB bandwidth. Thus, the transmitting response can be calculated by using the input mechanical impedance. Moreover, the equivalent electrical circuit can be also established by the determined lumped parameters.

Discharging is the most available method to judge the storage battery. The actual capacity could be calculated by the discharging current and time. It is expounded that the design and test for intelligent discharging monitor and control system based on ARM +CPLD. The system can perform the test and discharging timely in the way of constant current or resistance. What's more, it can detect automatically the single battery and check and analyze the capacity exactly. The design scheme and principle are described in this paper too. Furthermore it is illuminated mainly that CPLD logic control, A/D sample, RS485 communication for parallel monitor, check and discharging and current regulating. Then the software is designed for the system and it is presented that the program for check and discharging test and current regulation. Finally the result of system test is given.

This paper introduces a new high sensitivity micromachined gyroscope. It is an integrated micromechanical vibratory rate gyroscope based on resonant sensing of the Coriolis force. And it has many advantages over rate gyroscopes that utilize displacement sensing for rotation rate measurement. These advantages include a quasi-digital FM (frequency modulation) output, high resolution, large dynamic range, good linearity, low noise and low power consumption. As a whole, the structure includes proof masses, cantilevers, leverage mechanisms, DETF (double-ended tuning fork), driving and checking combs. The structure parameters' influences on capability parameters are analyzed by MATLAB, the mechanical and model analysis of structure are carried out by ANSYS. At first, we have done the modal analysis in order to make sure the first modality of the structure is the working modality. At the same time, we change some parameters to let the frequencies of other interference modalities much higher than that of the working modality. Then, the harmonic analysis is made to get the information of the sensitivity of the structure. Verified from the simulation results, the sensor can successfully realize the purpose of high precision.

Two-phase flow is a kind of mixed ambulatory regime which exits widely, such as the oil-gas and oil-water two-phase flow in the petroleum industry, and the gas-solid two-phase flow of the reaction unit of the fluidized bed in the chemical industry. Electrical capacitance tomography (ECT) technique is a new technique for two-phase flow measurement. This paper investigates the identification of flow regimes for gas-liquid two-phase flow using soft-sensing technique which is based on ECT and artificial neural network. Using ECT and artificial neural network technique, an online soft-sensing model used to identify flow regimes of gas-liquid two-phase is built. Using a two-layer self-organizing competitive neural network, a mathematic relationship between the second variable (the character parameters extracted from ECT sensor outputs) and primary variable (the flow regime of gas-liquid two-phase flow) of the soft-sensing model is built. After that, the identification of flow regimes for gas-liquid two-phase flow can be realized. Simulation results show that the proposed method has good identification precision and fast identification speed, which means it is an effective tool in two-phase flow regime online identification.

This article analyses nowadays in common use of football robots in China, intended to improve the football robots' hardware platform system's capability, and designed a football robot which based on DSP core controller, and combined Fuzzy-PID control algorithm. The experiment showed, because of the advantages of DSP, such as quickly operation, various of interfaces, low power dissipation etc. It has great improvement on the football robot's performance of movement, controlling precision, real-time performance.

Benefited from digital interface of electronic transformers, information sharing and system integration in substation can be realized. An embedded system-based digital output scheme of electronic transformers is proposed. The digital interface is designed with S3C44B0X 32bit RISC microprocessor as the hardware platform. The μCLinux operation system (OS) is transplanted on ARM7 (S3C44B0X). Applying Ethernet technology as the communication mode in the substation automation system is a new trend. The network interface chip RTL8019AS is adopted. Data transmission is realized through the in-line TCP/IP protocol of uClinux embedded OS. The application result and character analysis show that the design can meet the real-time and reliability requirements of IEC60044-7/8 electronic voltage/current instrument transformer standards.

According to the technological process and the requirement for system control of the GLP Laboratory, an automatic system is designed to monitor and control over the environment parameters of the GLP laboratory. The system is composed of a programmable controller and touching screen as the processing unit. The Schneider PLC TSX P57303 controller with its counterpart input/output modules is adopted as the hardware platform and the Schneider PL7-MICRO/WIN as the software platform. This paper presents the main flow process design of the control system. The test results show that the control system can run automatically and switch mutually under different modes, and the functions such as monitor and control over the environment parameters of the GLP laboratory are realized.

An intelligent pressure analysis system was designed based on the improved bedsore prevention mattress. The system can recognize the area of the human body that need to be massaged according to the maximum pressure and its duration in each area. The pressure signals are measured from the sensors in different mattress areas, after they are sampled and then sent to the computer by serial port, the main functions of the system, such as data storage and real time analysis, will be implemented in the designed LabVIEW virtual instrument. The changes of pressure signals and the state in each area of the human body can be visually displayed by the virtual instrument, and that is useful for clinic observation.

Electromagnetic Tomography (EMT) is a non-contacting method for acquiring information of conductivity in physiological area. The interest conductivity range is from 0.1s/m to 2s/m. Electromagnetic Tomography model of sensor is set up in COMSOL and the relation between conductivity and measurement is analyzed and presented. The paper puts forward two evaluating standards for optimum design of sensors involving calculated sensitivity on conductivity and signal /carrier ratio (SCR). Simulation on sensing field reflects the linear relation between conductivity and in-phase or real parts of detective voltages, and simulation on sensors' configuration including sensor location and coils' diameter render the object of sensor optimum design become more valid Simulative data are analyzed elaborately and rationally and finally the author provides the reference range for EMT sensors' configuration. The optimum design of sensor array could acquire significant information of the object field and consequently is beneficial to the further image reconstruction of EMT.

Micro-accelerometer structure is one of common MEMS devices. Its performance and characteristic couldn't be detected in the package. Under the impact of static load shock, dynamic harmonic load shock and temperature variation, the response were investigated. When static load was applied on the top of the micro-accelerator, its displacement and contact force that applied on the bottom increased nonlinearly with the input load increased. While the dynamic harmonic load applied on micro-accelerator, the changes of the generalized acceleration, generalized displacement, generalized velocity, phase acceleration, phase displacement, phase velocity in six modes with different wave frequencies were gained in mode analyses. The impact of temperature on device performance was investigated and the ideal work environment temperature was obtained.

High force update rate is a key factor for achieving high performance haptic rendering, which imposes a stringent real time requirement upon the execution environment of the haptic system. This requirement confines the haptic system to simplified environment for reducing the computation cost of haptic rendering algorithms. In this paper, we present a novel "hyper-threading" architecture consisting of several threads for haptic rendering. The high force update rate is achieved with relatively large computation time interval for each haptic loop. The proposed method was testified and proved to be effective with experiments on virtual wall prototype haptic system via Delta Haptic Device.

There are problems of poor characteristics on control and operation for existed hyperthermia equipment. This paper designs a temperature control system for the perfusion hyperthermia equipment. In this system, LCD and touch keys are used as the man-machine interface, and C8051F020 is used as main control, FPGA is used as main high speed memory, using gray forecast fuzzy PID control algorithm. And the equipment can realize control accuracy of 43±0.2 degree Celsius. This paper introduces the design of hardware and software of the temperature control for the hyperthermia equipment.

Inertial navigation system (INS) plays a significant role in aeronautics and spaceflight. At present the traditional domestic test equipments of INS are mostly outdated with a deficiency of automatization. And the majority of test equipments are just able to test a specific type of INS, which results in very low efficiency, and wastes a large number of hardware resources. This paper introduces a kind of INS integrated test system based on virtual instruments, and gives the design methods of the system software. The application of the system enhances the intelligence and automatization of test devices, and has the ability of testing different types of inertial navigation devices.

New Geometrical Product Specifications (GPS) is the foundation of the technology standards and metrology specifications of mechanical and electric products. GPS estimation of uncertainty in CMM (coordinate measuring machine) measurement can improve the reliability of the verification result. In this paper, a method to estimate the uncertainty in cylindricity CMM measurement is proposed according to the requirements of new GPS standard system. Based on the transparent box model given in ISO/TS 14253-2, the calculation equation of the uncertainty in cylindricity CMM measurement is deduced. And the decision rule based on the compliance uncertainty is adopted to decide whether the cylinder can be accepted or not. The experimental result indicates that the method can not only assure the integrity of the verification result, but also improve the reliability of verification.

The airborne recorder is the key device to store important data occurring in the answering machine responder in an identification communications. To overcome the limit of the previous recorders and store data more accurately and convenient, a new recorder is necessary to solve this problems. In this article, the whole design and operation process of the new recorder is introduced, including the software and hardware design program procedure and programming thoughts.

In order to study the temporal and spatial evolution characteristics of gas-liquid two-phase flow pattern, the two-phase flow monitoring system composed of high-speed dynamic camera and Vertical Multi-Electrode Array conductance sensor (VMEA) was utilized to shoot dynamic images and acquire the conductance fluctuating signals of 5 typical vertical gas-liquid two-phase flow patterns in a 125mm i.d. upward pipe. Gray level co-occurrence matrix (GLCM) was used to extract four time-varying characteristic parameter indices which represented different flow image texture structures and also Lempel-Ziv complexity of them were calculated. Then the transition of flow structure and flow property were comprehensively analyzed, combining the result derived from image information with recurrence plots (RPs) and Lempel-Ziv complexity of conductance fluctuating signals. The study showed that the line texture structure of RPs enabled to indicate flow pattern characteristics; the flow image texture structure characteristic parameters sequence described the variance of flow structure and dynamical complexity of different flow patterns.

A new current-mode universal biquadratic filter with three inputs and one output is presented. The proposed filter based on only two multi-output second-generation current controlled conveyors (MO-CCCII), two grounded capacitors and two grounded resistors, can realize five standard filter functions of high-pass, band-pass, low-pass, notch and all-pass from the same configuration. The simulated natural frequency f0 31.8KHz of the filter can be tuned electronically by adjusting the bias currents of the MO-CCCIIs, No critical matching conditions are required for all the filter response realizations. The performance of the proposed biquadratic filter was examined by PSPICE simulation.

Calibration of machine tools refers to the process of determining the relation between output and the value of input quantity. It refers to the system of conformity testing based on metrological characteristics. Parametric calibration is the only comprehensive indicator which depicts a detailed picture regarding accuracy of machine tool. In this paper the most important parametric errors of coordinate measuring machines (CMMs) were calibrated through transfer standards and by implementing conventional methods and techniques, in the sense that modern sophisticated instrument like laser interferometers are expensive and beyond the economical range of small industries besides they need comprehensive training and strong background knowledge for error prediction and analysis. In this scenario it is imperative to develop and implement some easy to use and cost effective efficient methods by exploiting the available resources. The methodology was implemented on a three coordinate measuring machine as per standard procedures of error measurement under controlled environment. Obtained results were reported for its further use to compensate the parametric errors, either physically compensation or correction in the measurement results.

Fault tolerant target localization is an important issue in wireless sensor networks. Faulty sensor nodes generate arbitrary data, which make the cooperation result untrustworthy. In this paper, multi-party cooperation between sensor nodes is used to estimate the target location robustly and accurately. We assign each sensor node a reliability level (RL) to qualify its data fidelity. A RL-weighted scheme is used to select the sensor node nearest to the target to perform as a processing node, which executes a particle swarm optimization algorithm to solve the maximum likelihood function of target location distribution. Each sensor node's RL is then updated according to the current data quality determined by the estimated target location. Experimental results show that although more than 50% sensor nodes are faulty, target localization error decreases over time and ultimately achieve a low level.

The design and implementation methods for information collection and wireless transmission equipment of public electric vehicle are discussed. To the hardware system, the hardware configuration and functions are discussed and the important circuits design are given. To the software system, the design methods for receiving position data from GPS receiver and wirelessly transmitting data based on the GSM short message are especially discussed. The practical applications show that the equipment is applicable to the electric vehicle and the design methods are very valid and practicable.

In this paper, an application of genetic algorithm (GA) which makes the spectra of malignant tissue and that of normal tissue cluster respectively is investigated. Cluster analysis is a typical optimization problem of permutation and combination. The results of traditional algorithms closely depend on whether the parameters are rightly set. Besides, the physical understanding of sample spectra which has not been clearly known is usually needed to obtain a better result. The high dimension of the spectral data also adds difficulty in the analysis. Thus, it is almost impossible to set every parameter properly. Furthermore, since the variables and object functions are always discrete, there are a mass of local extremums. Conventional methods have no good strategy to deal with these inferior solutions. Therefore, the final cluster result is greatly influenced by the initial cluster centers and the order how the samples are input. Genetic algorithm is established based on the theory of nature selection and evolution. For GA, the understanding of the physical meaning is not necessary. Meanwhile, GA performs in a considerable high efficiency way. In the experiment, the sum of the inter-cluster distances is regarded as the object function. After smoothing, standard normal variate (SNV) processing, and outlier detection on sample spectra, Principal component analysis (PCA) is processed. Then selection, mutation and crossover are carried out on chromosomes whose ith bit value indicates which class sample i belongs to. Once the GA clustering is finished, tissue samples could be easily discriminated based on the characteristic absorbance peaks of protein, fat, nucleic acid and water. In this paper, three kinds of clustering algorithms are processed, and it shows that comparing to the conventional method, GA obtains a better result.

Designing a micro, high reliability weak signal extracting system is a critical problem need to be solved in the application of silicon resonant micro-sensor. The closed-loop testing system based on FPGA uses software to replace hardware circuit which dramatically decrease the system's mass and power consumption and make the system more compact, both correlation theory and frequency scanning scheme are used in extracting weak signal, the adaptive frequency scanning arithmetic ensures the system real-time. The error model was analyzed to show the solution to enhance the system's measurement precision. The experiment results show that the closed-loop testing system based on FPGA has the personality of low power consumption, high precision, high-speed, real-time etc, and also the system is suitable for different kinds of Silicon Resonant Micro-sensor.

A high speed CMOS image acquisition and transmission system, which is composed of CMOS image sensor IBIS5-A-1300, USB 2.0 interface chip EZ-USB FX2 and FPGA (Field Programmable Gate Array), is designed and developed. The design of IBIS5-A-1300 driving timing, USB interface chip timing, firmware and application program are introduced. Experiments show that the system possesses the advantage of high resolution and high frame rate, supports single frame acquisition and video preview and fits the criterion of USB2.0 and the demand of real-time data transmission.

This paper introduces a new decoupled micromachined gyroscope. It is based on resonant sensing of the Coriolis force, which has many advantages over rate gyroscopes that utilize displacement sensing for rotation rate measurement. These advantages include a quasi-digital FM (frequency modulation) output, high resolution, good linearity, and low noise. As a whole, the structure includes two proof masses, cantilevers, leverage mechanisms, DETF (double-ended tuning fork), driving and checking combs. The mechanical and model analyses of structure are carried out by ANSYS. At first, we have done the modal analysis in order to make sure the first modality of the structure is the working modality. At the same time, we change some parameters to let the frequencies of other interference modalities much higher than that of the working modality. Then, the harmonic analysis is made to get the information of the sensitivity of the structure. Verified from the simulation results, the sensor can successfully realize the purpose of decoupling.

Data fusion technology is an efficient way to decrease network energy consumption and recognition uncertainty of single sensor node for clustering wireless sensor networks. However, Dempster's combination rule may induce illogical results, when the information from different intra-cluster nodes highly conflict due to the background noise or flaws of the sensor itself. Through analyzing all evidences collected by cluster header, a novel aggregation algorithm based on support degree coefficient and conflict intensity is proposed. In the method, conflict intensity between every two bodies of evidence was analyzed, which divides conflict probability into useful and useless information respectively. In order to weaken the effects of abnormal evidences on fusion result, the combination sequence is made to be descending sort according to total conflict intensity of evidence. Additive strategy is adopted to obtain the support degree coefficient of single focal element of evidence set, based on which the useful information is assigned to different certainty propositions respectively. Numerical example showed that the proposed algorithm can provide more reasonable results with good convergence compared with other several modified combination rules.

This paper designs a digital closed-loop system on FPGA, aiming at silicon resonant pressure micro-sensor, which is inspirited by electricity, and picked up by resistances. This closed-loop system uses a method integrated by correlation detection and frequency scan to detect the resonance frequency of sensors, and then achieves pressure detection. Experiments have validated that this system can detect the resonance frequency of sensors effectively, overcoming the feebleness output signal and low SNR(signal noise ratio).

Involute helicoid is widely used in engineering and its accurate measurement is a focused research subject for improving its application. The analytic representation of involute helicoid under Cartesian coordinate system is established according to its formation principle. The surface error model for assessing the profile error of involute helicoid is discussed according to differential geometry characteristic. Finally a practical measurement of an involute worm is conducted with a coordinate measuring machine and the surface profile error evaluation is provided according to the surface error model for validating the feasibility and practicability thereof.

This paper introduces an a practical silicon beam resonator attached to an E-type round diaphragm, which is used for measuring the concentrated force. Working principle of this sensor in introduced and relationship between the basic neutral frequency of the beam resonator and the concentrated force are analyzed and investigated. FEM (Finite Element Method) simulation is used to simulate the vibration features of the above beam resonant and the microsensor. Finally, based on the differential output mean, a set of optimum parameters of the above sensing unit is determined.

In this paper, a new calibration method is proposed to fulfill the requirement of calibration of electronic transformer. At first, the fast measurement method of power frequency is presented. And then the principle of Quasi-synchronous DFT algorithm is introduced in order to satisfy the special requirement of fast harmonic analysis during the calibration of electronic transformer. Therefore the amplitude error and phase error of electronic transformer could be obtained based on this new calibration method. The performance of method is verified by simulation results.

A novel actuator of small angle control is researched and designed in this paper, which can be used in micro optical electro-mechanical system (MOEMS) gyroscope. This actuator is composed of three pieces of piezoelectric ceramics (PZT), foundation base and gear frame. According to converse piezoelectric effect, dilations of the PZT change when applied voltages are different which leads actuator to have a deflection angle. Connected with control circuit, actuator has the ability to exactly adjust angle which has arc-second level. It can accomplish the adjustment of spatial resonator with high efficiency. Structure model of the actuator was set up, and simulation was completed in this paper. Also the performance of actuator was validated by experiment.

Optimal design of motor and gear for high load acceleration becomes very simple if the fact is used that an ideal gear transfers the product of torque and acceleration unchanged just like the product of torque and speed. Due to this analogy torque demand for acceleration of load inertia can be investigated in the same way as torque-speed requirement for constant speed operation of the load. In contrast to the conventional mathematical method which is based on calculation of extreme values of acceleration the new method delivers very simple design rules in particular when stationary load torque cannot be neglected. Furthermore, consideration of torque-acceleration diagrams leads to a deep insight in the design process which enables to modify the design if required.

This paper proposed a novel method of sensing the weak differential capacitance change of Micro-Electro-Mechanical Systems (MEMS) accelerometer with sandwich structure. The detection circuit mainly consisted of frequency selective networks, Phase Locked Loop (PLL), logical gate and low-pass filter. The two elemental capacitances of differential capacitance respectively harmonic oscillated in two parameter symmetry resonance units. Beating wave represented when the two output signals with different frequency had passed the logical gate and low-pass filter in turn. The frequency of beating wave was proportional to the sensing differential capacitance. One of the most important aspects of using circuit resonance elements with MEMS technology was the elimination of analog voltage amplitude measurement used in conventional MEMS accelerometers. On the other hand, this method overcame the disadvantages of conventional mechanical resonance accelerometers, with frequency output and high Signal Noise Ratio (SNR), such as poor dynamic response, temperature drift, complex structure and large power dissipation. According to the numerical simulation results, the circuit resonance detector with PLL can reach high capacitance resolution: 10^-16 F.

Structural Health Monitoring (SHM), which can realize real time testing and online testing for structure, is a new research field in test technology. To solve the bolt damage detection and position in large structures, this paper researches on the application in SHM, by using piezoelectric sensor array to fix damage position and wavelet packet analysis to pick-up damage eigenvalue. The wavelet packet theory is expounded and the optimal wavelet function for structural damage detection is discussed. Using wavelet packet analysis to decompose the energies in each band of frequency in the sensor signal, the damage eigenvalue is extracted out. The damage position method by piezoelectric sensor array is discussed. In the end, an experiment of bolt loose damage detection and position is carried out. The results indicate that the structural health monitoring based on piezoelectric sensor array is quite effective.

Bone cells live in an environment heavily influenced by mechanical forces. The researches of bone cell responses in hard scaffolds under differently mechanical conditions will be greatly beneficial to elucidating the mechanisms of bone mechanotransduction as well as applications of mechanical condition in bone tissue engineering. However, the appropriate device for the experiments is prerequisite. A loading device suitable to hard scaffold for study on mechanical responses of bone cells was made by usage of a kind of long-travel, high-load piezoelectric actuator. The device, which is so small enough to work in a standard incubator, can cause hard scaffolds with directly uniaxial compressive strains with more magnitudes, frequency components, and waveforms, including bone physiologically mechanical state, precisely controlled by a computer. The device achieves precise mechanical conditions by testing verification. The device may produce a model that will be suitable for investigating the influences of mechanical responses on bone cells in 3D hard scaffolds in vitro matching that in cancellous bone in vivo and may be applied during bone tissue engineering culture.

A new method for wet gas metering with a long-throat Venturi tube is presented. Correlations between the differential pressures (DP) of the convergence segment and straight segment of the tube and the parameters of gas-liquid two-phase flow are obtained by combining models of orifice and Venturi meters for wet gas metering. A prototype device of the Venturi-based wet gas meter has been designed and constructed. The calibration of the discharge and modification coefficients are accomplished through experiments. Experimental results show that the long-throat Venturi meter can be used to measure the wet gas with a mass quality from 0.06 to 0.412.

The electron analyzer is one of the analyzer of plasma package that will be developed for Mars exploration. It is to analyze the distribution of electron's energy and direction around the orbit of spacecraft. The article gives the detailed design of the analyzer.

Artesunate is a very effective drug to treat malaria. They are studied experimentally by Terahertz (THz) time-domain spectroscopy (THz-TDS), and the characteristic absorption spectra are obtained in the range of 0.2 to 2.6 THz. The vibrational frequencies are calculated using the density functional theory (DFT). Theoretical results show that 0.71, 1.94 and 2.46 THz are significant agreement with the experimental results in 0.87, 1.82 and 2.46THz, and identification of vibrational modes are given. The calculated results further confirm that the characteristic frequencies come from the collective vibrational modes. The results suggest that the use of the THz-TDS technique can be an effective way to inspect for Chinese medicine.

Radial composite deviations can be assessed by the traditional double-flank gear rolling tester, but it is hard to obtain tangential deviations (helix, taper, etc.) of the produced gear. To solve this problem, a measuring principle of the double-flank gear rolling test with many degrees of freedom was investigated in order to inspect radial composite deviations and tangential deviations during one inspection. This paper presents the measuring model, the definition of the deviations and the evaluation method, including the radial composite helical slope deviation and the radial composite helical taper deviation. An In-line Gear Measuring Machine (GMM) was developed based on this measuring principle to meet the demand of high-speed inspections in mass-production gear workshops.

To increase the accuracy of applying traditional fault diagnosis method to aeroengine vibrant faults, a novel approach based on wavelet neural network is proposed. The effective signal features are acquired by wavelet transform with multi-resolution analysis. These feature vectors then are applied to the neural network for training and testing. The synthesized method of recursive orthogonal least squares algorithm is used to fulfill the network structure and parameter initialization. By means of choosing enough practical samples to verify the proposed network performance, the information representing the faults is inputted into the trained network. According to the output result the fault pattern can be determined. The simulation results and actual applications show that the method can effectively diagnose and analyze the vibrant fault patterns of aeroengine and the diagnosis result is correct.

The Simulink debugger has the advantage of running a simulation model step by step to examine the results of executing a specific method. Integrating the Simulink debugger into the .NET platform and controlling it in the host application will undoubtedly increase the interactivity. A novel approach to integrate the Simulink model and the built-in debugger with .NET platform was introduced to enhance interactivity for designing simulation applications. And a case study for basic hydraulic pump system simulation was presented as a demonstration. The revealed result of the test application has proven that the method is feasible and practical.

This work proposes an algorithm to measure the smoothness of three-dimensional object. Firstly use computer vision technology to reconstruct the three-dimensional surface. Then construct high order vanishing moment wavelet to analyze the data. In order to detect the discontinuous derivative points, this paper proposes an algorithm based on wavelet transform. Wavelet is used to descript surface smoothness and detect abnormal data. When using different vanishing moment wavelets to deal with data, we would get different value at those points with different smoothness value. That surface with same smoothness would become a plane. Meanwhile, in order to improve the algorithm validity, this paper proposes using Daubechies wavelet. This algorithm resolved our project problem. It can be used in other projects that require the surface with good smoothness.

A Gaussian radial base function (RBF) neural network forecast on signals in the Aloe vera var. chinensis by the wavelet soft-threshold denoised as the time series and using the delayed input window chosen at 50, is set up to forecast backward. There was the maximum amplitude at 310.45μV, minimum -75.15μV, average value -2.69μV; and <1.5Hz at frequency in Aloe vera var. chinensis respectively. The electrical signal in Aloe vera var. chinensis is a sort of weak, unstable and low frequency signals. A result showed that it is feasible to forecast plant electrical signals for the timing by the RBF. The forecast data can be used as the preferences for the intelligent autocontrol system based on the adaptive characteristic of plants to achieve the energy saving on the agricultural production in the plastic lookum or greenhouse.

The manipulating test-bed is a typical parallel mechanism, in which the three actuators move according to given regulation to change the gesture of swash plate. Directing to the triangle distribution of three actuators, the characteristic of the test-bed structure was analyzed, and the function of this test-bed was investigated. The coordinate system of the parallel mechanism was established, and the freedom of the parallel mechanism was calculated. According to the analysis of the manipulating test-bed aforementioned, the restriction condition of the parallel mechanism was analyzed when the gesture of the swash plate changed, and then the forward and inverse position solution were given. The position solution will guide the actuator control of test-bed with high precision.

Automatically Switched Optical Network (ASON) is currently a new and hot research subject in the world. It can provide high bandwidth, high assembly flexibility, high network security and reliability, but with a low management cost. It is presented to meet the requirements for high-throughput optical access with stringent Quality of Service (QoS). But as a brand new technology, ASON can not be supported by the traditional protocol software and network equipments. And the approach to build a new ASON network on the basis of completely abandoning the traditional optical network facilities is not desirable, because it costs too much and wastes a lot of network resources can also be used. So how to apply ASON to the current networks and realize the smooth transition between the existing network and ASON has been a serious problem to many network operators. In this research, the status in quo of ASON is introduced first and then the key problems should be considered when applying ASON to current networks are discussed. Based on this, the strategies should be complied with to overcome these key problems are listed. At last, the approach to apply ASON to the current optical networks is proposed and analyzed.

In order to overcome the weakness of traditional flatness defect pattern recognition by least squares method (LSM) proximity algorithm which is illegible on physical meaning and poor robust stability, as long as the low accuracy of common BP neuron network, a novel parallel flatness defect pattern recognition model based on binary tree hierarchical BP neural network and Legendre orthodoxy polynomial decomposition were presented, each node in the binary tree has the same structure but different weights. The precision of novel model was improved dramatically by classifying the prediction range and setting the binary tree depth. Experiment results show this novel hierarchical BP network performances are improved not only in precision but also in robust stabilization.

By means of wavelet transform and neural network, a novel approach for power quality (PQ) event classification is proposed. The feature vectors for various PQ events are extracted using wavelet transform which can accurately localizes the characteristics of signal in time-frequency domains. The feature vectors are then applied to the neural network for training and PQ pattern classification. The neural network have demonstrated promise in pattern recognition and been considered a potential alternative approach to pattern recognition It is concluded that the proposed neural network has better data driven learning and local interconnections performance by comparing with a classic neural network. The comparison between the proposed method and the other existing method is discussed. It is proved that the proposed approach can provide accurate classification results and give a new way for detection and analysis of power quality events.

The drainage system of mine has strict requirement to its equipments for the special work environment of the mine. The controllability of the shut-off valve is a key in the automatic drainage system. This paper presented the design scheme of the controllable shut-off valve according to the real condition of drainage system in mine. The paper built geometric model and mathematic model of the hydraulic controllable shut-off valve by using FLUENT dynamic mesh technology, and carried on the numerical simulation to its internal flow field, and analyzed the analog result. From the analysis results, it can see that, when the valve's closure or open velocity is bigger than 0.01 m/s, the phenomenon of pressure fluctuation and the water hammer would occur easily.

Single chip integrated power switching circuits can generate huge substrate noise, which impacts the circuit performance of noise sensitive blocks on the same chip. In this paper, the effects of several schematic and layout techniques to reduce substrate noise, including optimizing gate resistors and capacitors, merging NWELL of power devices, adding PEPI around NWELLs, using separated PADs for less noisy blocks, are validated by both simulation and silicon experiments.

Support vector machine (SVM) is a novel machine learning based on statistical learning theory, SVM is powerful for the problem with small sample, nonlinear and high dimension. A model of transformer diagnosis based on SVM is present in this paper in which it uses the grid search method based on cross-validation to determine model parameters. Taking into account the compactness characteristics of DGA data, the fuzzy C-means (FCM) clustering method is adopted to pre-select samples achieved. It solves the problem of long time expended on model parameters determined, and enhances a certain promotion of the model extension ability. Practical analysis shows that this model has a good classification results and extension ability.

To build the solid granule flowrate model by the simple dynamic recurrent neural network (SRNN) is presented in this paper. Because of the dynamic recurrent neural network has the characteristic of intricate network structure and slow training algorithm rate, the simple recurrent neural network without the weight values on recursion layer is studied. The recurrent prediction error (RPE) learning algorithm for SRNN by adjustment the weight value and the threshold value is reduced. The modeling result of solid granule flowrate indicates that it has fast convergence rate and the high precision the model. It can be used on real time.

This paper addresses a new and efficient behavioral modeling method of digital I/O ports for EMC and signal integrity simulations. The proposed modeling methodology is based on the fuzzy logic system from port voltage and current transient waveforms. The obtained models can be implemented as SPICE subcircuit conveniently and their accuracy and efficiency are verified by applying to the approach to the characterization of transistor -level models of actual devices.

X-ray images are the essential aiding means in clinical diagnosis of fracture all along. According to the characteristic of X-ray images, a novel improving strategy based on homotopy modification of gradients is proposed. Opening-by-reconstruction and closing-by-reconstruction are used to smooth the images. Top-hat transformation and bottom-hat transformation are used to enhance contrast. Combination of top-hat-reconstruction and opening-by-reconstruction is employed to remove complex muscle background. Extended minima transformation, area opening operation, image addition, complement of image, distance transformation and watershed transformation are together employed to compute internal and external markers. Using the markers to modify gradients ensures that the regional minima exactly occur in the bones objects and the muscle background. Correct watershed ridge lines are obtained by applying watershed transform to the modified gradients. Experimental results show that a good segmentation effect can be achieved using the proposed algorithm, and the algorithm is suitable for segmenting X-ray images in interactive fracture diagnosis systems.

For quantitative detection of distortions of voltage waveform, a novel approach based on wavelet transform (WT) to detect and locate the power quality (PQ) disturbances is proposed. Due to expansion of power electronics devices, the wide diffusion of nonlinear and time-variant loads has caused massive serious PQ problems in power system. The signal containing noise is de-noised by WT, and then become input node to the wavelet neural network. The standard genetic algorithm is utilized to complete the network structure, and then the fundamental component of the signal is estimated to extract the mixed information. Therefore the disturbance signal is acquired by subtracting the fundamental component. In processing of disturbances signal, the principle of singularity detection using WT modulus maxima is presented with dyadic WT approach for the detection and localization of the PQ. The simulation results demonstrate that the proposed method is effective.

In this paper, a means, which is based on Radial Basis Function Neural Network (RBFNN), is firstly presented to make the model for nonlinear systems. As an application example of this means, the high power DC graphitizing furnace is analyzed, and the RBF model for graphitizing furnace is constructed from experiments or simulations. The procedures for training the model are described along with discussions on error. Secondly, the open loop dynamic model is discussed in detail. The dynamic model of graphitizing furnace is accomplished in this paper. All the simulated results show that the discussed approaches are effective.

There are two problems to be solved in application of high frequency (HF) signal injection method in sensorless, low speed or position servo systems. One problem is that full torque startup needs precise estimation of static rotor position. Another is that the speed regulation range is confined since the estimation error grows while the rotor speed grows because of the phase lag comes from synchronous rotating filter. The effect on the accuracy of static rotor position estimation based on HF impedance model is analyzed in this paper and a novel impedance model instead of inductance model is utilized in static position estimation method to improve the static estimation precision. A simple phase compensation method is utilized to enhance the dynamic performance of the sensorless control system. Simulation results indicate that the established sensorless control system has both improved static and dynamic estimation accuracy. Meanwhile, the system has a strong tolerance of load disturbance which is vital for applications in low speed servo systems.

Face recognition is an essential work to ensure human safety. It is also an important task in biomedical engineering. 2D image is not enough for precision face recognition. 3D face data includes more exact information, such as the precision size of eyes, mouth, etc. 3D face database is an important part in human pattern recognition. There is a lot of method to get 3D data, such as 3D laser scan system, 3D phase measurement, shape from shading, shape from motion, etc. This paper will introduce a non-orbit, non-contact, non-laser 3D measurement system. The main idea is from shape from stereo technique. Two cameras are used in different angle. A sequence of light will project on the face. Human face, human head, human tooth, human body can all be measured by the system. The visualization data of each person can form to a large 3D face database, which can be used in human recognition. The 3D data can provide a vivid copy of a face, so the recognition exactness can be reached to 100%. Although the 3D data is larger than 2D image, it can be used in the occasion where only few people include, such as the recognition of a family, a small company, etc.

This paper investigates a new method for gas/liquid two-phase flow recognition by combining the features of wavelet energy and the recurrent artificial neural networks. The information of the method that provided by Cross-Sectional Measured Resistance Information (CSMRI) is the measured data in horizontal pipe. The feature vector of wavelet transform energy that can express the essential information of gas/liquid two-phase flow is constructed. The improved recurrent Elman neural network is brought forward to recognize the Gas/Liquid Two-Phase flow regime. The architecture of an Elman neural networks with the context units that memorize the past input feature value can express the time series. The obtained results indicate that the method is suitable to estimate the flow regime and the higher recognizing rate of the flow regime is obtained.

The hydraulic vibration system controlled by wave exciter is a mechanic-electric-fluid integration system, and it has high dynamic characteristics. Modeling and simulation for it has come to professional's attention in the field of hydraulic vibration industry, because it is nonlinear and complex. In this paper, a method has been proposed. By using power bond graph method, the bond graph model for it can be established, meanwhile, it is proposed that controlled parameters are considered to join the model, in order to control power flow alternated; and the mathematical model(state equations) of this system can be built according to bond graph theory and controlled relations; then simulation model can be built by using Matlab/Simulink software, the model can intuitively express system's power flow direction and controlled relations. To the question that stiff equation appears easily in model of hydraulic system, we can choose the adapting algorithm offered by Matlab software to obtain the more precise simulation results.

This paper proposes a low complexity near optimal antenna selection scheme based on minimum error rate to improve the performance of multiple-input multiple-output (MIMO) systems. For the independent and identically distributed (i.i.d.) channel, it only needs a sorted QR decomposition compared with the optimal antenna selection algorithm, which requires an exhaustive search of the pseudo inverse of the channel matrix. For the correlated channel, the proposed algorithm achieves good performance by utilizing correlated matrix characteristic. The novel algorithms achieve good performance that is very close to the optimal algorithm, decrease the computational complexity greatly, improve the performance of the receivers, and almost no capacity loss. Simulation results demonstrate that the proposed antenna selection algorithm achieve excellent performance.

Electrical impedance tomography (EIT) aims to estimate the electrical properties at the interior of an object from current-voltage measurements on its boundary. In this paper, preconditioned reconstruction algorithm which improves the property of iterative convergence has been proposed to solve the inverse problem of EIT. Experimental results indicate that the algorithm is much more stable and efficient compared with normal iterative methods. At the same time, the invertible preconditioners and prior information of human thorax have been discussed in this paper.

Hyperthermia is one of the effective methods to treat the bladder cancer. In the process of bladder cancer hyperthermia, the precise measurement and control of the temperature on tumor is one of the critical technologies for medical instruments. In order to achieve precise control of the temperature, the author incorporates the grey forecasting, fuzzy control and conventional PID control. In this article the author presents the fuzzy PID control strategy based on grey forecasting. That control strategy can be divided into three steps: firstly, build the fuzzy tuning rules by simulation and analysis and obtain the parameters of PID controller by reasoning, secondly, determine the control effect directly through the PID control law, and then put the grey forecasting into use online. Simulation results show that the strategy combining grey forecasting with fuzzy control is superior to fuzzy PID control. It has strong robustness and self-adaptive ability.

The searching phase factors of partial transmit sequence (PTS) algorithm can be formulated as a combinatorial optimization problem with some variables and constrains, thus a modified discrete particle swarm optimization (DPSO) is applied to search the optimal combination of phase factors in this paper. The hamming distance is used to adjust the velocity of particle swarm, which makes the phase factors always move to the best phase factors, thus the orthogonal frequency division multiplexing (OFDM) signals with good peak-to-average power ratio (PAPR) performance can be achieved with low search complexity. To validate the analytical results, some simulations have been conducted, showing that the proposed schemes can achieve good PAPR performance with low computational complexity.

In this paper, a novel ellipse extraction method based on edge segments formed by edge detection in an image is proposed. Edge segments are split into small pieces based on polygonal approximation and adjacent pieces are merged to elliptical arc segments according to the defined constrain. Then arc segments belong to the same ellipse are grouped into one arc segment by improved RANSAC algorithm. Finally, the accurate ellipse parameters are obtained by the least square fitting with those edge points lying on the same grouped arc segment. Experiments on synthetic and real images verify the good performance of the proposed method in the complex background images.

An study for the active vibration control of intelligent structures subject to external excitations using piezoelectric sensors and actuators is presented. A simply supported piezoelectric intelligent plate is used as the controlled structures. The transfer function model of intelligent plates is derived and an analogy for modal control between the piezoelectric structures and general ones is established. Based on this concept and by experiment development, a "quasi-independent modal control" technique is presented, attempting to approach, with hardware as simple as possible, independent modal control.

A novel multifunction second order current-mode filter employing two multiple output second-generation current controlled conveyors (MO-CCCII) and only two grounded capacitors is presented. The proposed circuit can simultaneously realize low-pass (LP), band-pass (BP), band-stop (BS) and high-pass (HP) filter functions from the same configuration without critical matching conditions. It can also realize all-pass (AP) filter function just by connecting the output currents I_LP, I_BP and I_HP without using any additional element. Electronic tunability for ω₀ and Q through adjusting the bias current of the MO-CCCII. Additionally, grounded capacitor is attractive for integration. A sensitivity analysis shows that the filter has low active and passive sensitivities. In the last, PSPICE simulation results are given to verify theoretical analysis.

Thermochromism vanadium dioxide thin films were fabricated by quick thermal oxidation annealing of direct current facing targets reactive magnetron sputtered vanadium oxide thin films at 300-360°C for 1-3h. X-ray diffraction shows the vanadium dioxide thin film was obtained annealed at 300°C for 1h, and the structure changed from monoclinic to tetragonal rutile VO2 at around 54°C. X-ray photoelectron spectroscopy and Fourier transform infrared spectroscopy show that the structure of VOx film underwent the following transformation: amorphous structure = VO₂ (B) + VO₂ (M) - VO₂ (M)+VO₂ (R).

The quantitative evaluation of detection algorithms performance is a key for the advancement of target detection algorithms. The receiver operator Characteristic (ROC) curve method is purposed to evaluate the detection algorithms performance for hyperspectral data in the basis of the analysis and comparison of kinds of evaluation methods. A ROC curve plots the probability of detection (PD) versus the probability of false alarm (PFA) as a function of the threshold, and the detection performance can be synthetically evaluated using the shape of ROC curve and the area under the curve. The algorithm and modeling method are presented in our work. The ROC curve is applied to evaluate the performance of independent component analysis (ICA), RX, gauss markov random field (GMRF), and projection pursuit (PP) algorithms for hyperspectral remote sensing data.

Spectral unmixing is a common problem in hyperspectral remote sensing, and it is a key issue of quantitative remote sensing. This article proposed a spectral unmixing algorithm based on spectral information divergence (SID) named SID-SMA. It could improve the precision of abundance estimation through choosing optimal endmember subset used in unmixing. SID-SMA adopted the idea of iteration and added the process of negative endmembers removing which could obviously reduce the computation complexity and improve the speed. Through the results of simulated data from spectral library, it could be seen that the correct proportion of endmember selection by SID-SMA was very high, arriving at 99.86% when the signal-to-noise ratio (SNR) was 100:1. From the point of abundance estimation errors, the algorithm presented here had lower value than two other methods. Especially, when the SNR was 100, the error was less than 0.05.

Gait recognition is new biological identity technology and widely researched in recent years for its many advantages compared with other biological identity technology. In this paper, we propose a simple but effective feature-compactness for gait recognition. First an improved background subtraction algorithm is used to obtain the silhouettes. Then the compactness is extracted from the images in the gait sequence as the feature vector. In the step of classification, DTW algorithm is adopted to adjust the feature vectors before classifying and two classifiers (NN and ENN) are used as classifiers. Because of the simple features which we choose, it consumes little time for recognition and the results turn out to be encouraging.

A novel method to detect power quality event in distributed power system combing wavelet network with the improved back-propagation algorithm is presented. The paper tries to explain to design complex supported orthogonal wavelets by compactly supported orthogonal real wavelets, and then explore the extraction of disturbance signal to obtain the feature information, and finally propose several novel wavelet combined information to analyze the disturbance signal, superior to real wavelet analysis result. The feature obtained from WT coefficients are inputted into wavelet network for power quality disturbance pattern recognition. The power quality disturbance recognition model is established and the improved back-propagation algorithm is used to fulfill the network parameter initialization. By means of choosing enough samples to train the recognition model, the type of disturbance can be obtained when signal representing fault is inputted to the trained network. The results of simulation analysis show that the complex wavelet transform combined with wavelet network are more sensitive to signal singularity, and found to be significant improvement over current methods in real-time detection.

Hair removal from skin melanoma image is one of the key problems for the precise segmentation and analysis of the skin malignant melanoma. In this paper, an automatically hair removal algorithm in dermoscopy images of pigmented skin lesions is proposed. This algorithm includes three steps: firstly, the melanoma image with hairs are enhanced by morphologic closing-based top-hat operator and then segmented through statistic threshold; secondly, the hairs are extracted based on the elongate of connected region; thirdly, the hair-occluded information is repaired by replacing the hair pixels with the nearby non-hair pixels. As a matter of fact, with the morphologic closing-based top-hat operator both strong and weak hairs can be enhanced simultaneously, and the elongate state of band-like connected region can be correctly described by the elongate function proposed in this paper so as to measure the hair effectively. Therefore, the unsupervised hair removal problem in dermoscopy melanoma image can be resolved very well through combining the hair extraction with information repair. The experiment results show that various hairs can be extracted accurately and the repaired effect of textures can satisfy the requirement of medical diagnosis.

Multi-pose ear recognition is a challenging problem of ear recognition technology. In this paper, the method based on locally linear embedding (LLE) and nearest feature line (NFL) is proposed by analyzing the disadvantages of most 2D ear recognition methods currently when dealing with poses variation and the shortcomings of the nearest neighbor (NN) classifier. The LLE algorithm is used to extract the ear feature, and then the NFL classifier is applied to classify ear images under varying poses. By contrast, experimental results show that the method based on LLE and NFL can obviously improve the recognition performance, which demonstrates the validity of this method.

In order to research on the algorithms and the error identity of star guidance, the emulator of star guidance is presented, which is a sub system of new integration navigation emulator based on RT-LAB. In this paper, a method of modeling star guidance emluator is presented; it makes use of the Embedded MATLAB Function of Simulink. With this modeling method, high efficiency of modeling, good readability and easy maintenance are obtained. Many other modeling methods are not supported by RT-LAB, because the real-time code is not available. The simulation results show that the proposed method of modeling is right; the emulator of star guidance can be compiled and translated into real-time code by MATLAB, which can be supported by RT-LAB.

Fault tree (FT) is usually a reliability and security analysis and diagnoses decision model. It is also in common use that expressing fault diagnosis question with fault tree model. But it will not be changed easily if fault free model was built, and it could not accept and deal with new information easily. It is difficult to put the information which have nothing to do with equipment fault but can be used to fault diagnosis into diagnostic course. Bayesian Networks (BN) can learn and improve its network architecture and parameters at any time by way of practice accumulation, and raises the ability of fault diagnosis. The method of building BN based on FT is researched on this article, this method could break through the limitations of FT itself, make BN be more extensively applied to the domain of fault diagnosis and gains much better ability of fault analysis and diagnosis.

The research of Chinese characters cognition is an important research aspect of cognitive science and computer science, especially artificial intelligence. In this paper, according as the traits of Chinese characters the database of Chinese characters font representations and the model of computer simulation of Chinese characters font cognition are constructed from the aspect of cognitive science. The font cognition of Chinese characters is actual a gradual process and there is the accumulation of knowledge. Through using the method of computer simulation, the development model of Chinese characters cognition was constructed. And this is the important research content of Chinese characters cognition. This model is based on self-organizing neural network and adaptive resonance theory (ART) neural network. By Combining the SOFM and ART2 network, two sets of input were trained. Through training and testing methods, the development process of Chinese characters cognition based on Chinese characters cognition was simulated. Then the results from this model and could be compared with the results that were obtained only using SOFM. By analyzing the results, this simulation suggests that the model is able to account for some empirical results. So, the model can simulate the development process of Chinese characters cognition in a way.

Ear recognition based on the force field transform is new and effective. Three different applications of the force field transform were discussed in this paper. Firstly, we discussed the problem in the process of potential wells extraction and overcame the contradiction between the continuity of the force field and the discreteness of intensity images. Secondly, an improved convergence-based ear recognition method was presented in this paper. To overcome the problem of threshold segmentation, an adaptive threshold segmentation method was used to find the threshold automatically; to reduce the computational complexity, a quick classification was realized by combining the Canny-operator and the Modified Hausdorff Distance (MHD). Finally, the algebraic property of force field was combined with Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) together to obtain feature vectors for ear recognition. We tested these applications of the force field transform on two ear databases. Experimental results show the validity and robustness of the force field transform for ear recognition.

As a heterogeneous nature material, there are unknown nonlinear relationships existing in the wood physical property modeling. To solve the complex nonlinear relationship of modeling parameters, an optimization algorithm of neural network based on Gauss-Chebyshev for wood physical property modeling is presented in this paper. The density of wood ring and moisture content are considered as the model inputs, while wood vertical elastic modulus as the output. By comparison the performance between Gauss neural network and Gauss-Chebyshev neural network, the latter is convergence fast with high generalization ability and approximation accuracy of the model.

We propose a novel wave field separation approach in this paper. Firstly, the arrival times and amplitude intensity coefficients of the reflected waveforms of underground interfaces are estimated by least square fitting. And then, the forward modeling of the seismic data are calculated and corrected to zero offset with the corresponding seismic wavelet and reflective parameters. The reflected waveform sequences which are compressed in large offset traces are effectively separated without any stretching distortion, which always exists in the results of traditional NMO. And the large offset traces can play a more important role in posterior stacking processing.

According to the request of automatic analysis and depressing high frequency interference of the ECG signals, this paper applies low-pass filter to preprocess ECG signals, and proposes a QRS complex detection method based on wavelet transform, which takes advantage of Marr wavelet to decompose and filter the ECG signals with Mallat algorithm, using the relationship between wavelet transform and signal singularity to detect QRS complex with amplitude threshold method in scale 3, and to detect P wave and R wave in scale 4. Meanwhile, compositive detection method is used for re-detection, thus to improving the detection accuracy ratio. At last, records from ECG database of MIT/BIH which is widely accepted in the world are used to test the algorithm. And the result shows that correction detecting ratio under this algorithm has been more than 99.8 percent. The detection method in this paper is simple and running fast, and is easy to be realized in the real-time detecting system using for clinical diagnosis.

Because of ear's special physiological structure and location, it is reasonable to combine ear with profile face for recognition in such scenarios as frontal face images are not available. In this paper, a novel method of multimodal recognition fusing ear and profile face based on kernel principal component analysis is proposed. With the algorithm, the fusion feature vectors of ear and profile face are established and nonlinear feature fusion projection could be implemented. The experimental results show that multimodal recognition fusing both ear and profile face results in improvement over either ear or profile face unimodal recognition.

Equipped with the mini camera, UAVs can be used as a surveillance device, which can be widely used in both civil fields as well as military fields. The real time video output by camera can be transferred down to the ground station and is processed to detect and localize the interested targets. A low-cost and real time circular targets detection and localization algorithm is proposed in this paper. The target is detected by image analysis based recognition method and the position is represented in UAV's coordinate frame. Further, the position is transferred to the world coordinate frame by using UAV's guidance data (position and attitude) to localize the targets. Experiment results are also given and show that the algorithm can be run in real time.

Analog signal circuit is the necessary component of modern electronic products. The research on the testability of analog signal circuit becomes the highlighted topic. In this paper, the modeling types are first discussed, then several different testability analysis based on different modeling methods are systematically summarized and explained, which includes numerical analysis method, symbolic analysis method, pole-zero analysis method, TTF method, CCM method, DES method, single dependency method, multi-signal method. As for every method, the basic idea, the research status, the practice and application instances, and the advantage/disadvantage are involved. At last, the future research topics are predicted.

In view of features of motion blurred images, a new robust blind restoration method with high fidelity is proposed in this paper, which can preserve image details and textures effectively. Compared with other restoration methods for motion blurred images, the new approach is characterized with a good property that no prior experience knowledge required. Meanwhile a new robust cepstrum-based PSF identification method is combined with a fast robust total variation-based restoration method to come into being an effective algorithm provided with high fidelity. A series of experiment results with artificial blurred images and natural blurred images verify the outstanding processing effect.

Focused on the problem of distortion correction for those images having simple contour, the synthetic method was described. In advance, without known camera parameters and any known world coordinates point in 3D space, the first order radial distortion coefficient can be estimated based on the fundamental property: a camera follows the pinhole model if and only if the projection of every line in space onto the camera is a line. Then the proposed distortion correction method, which characterized by its fast computing speed and good accuracy, maps not only pixel coordinates but also the grey values between the distortion image and non-distortion image. Several experiments and analysis were performed and presented on this paper. Finally, a comparative analysis about the accuracy and computational load with real data between this new method and the existed methods was put forward.

The design, component selection, fabrication, testing, and evaluation of an optically-switched, binary, fiber optic programmable delay line are discussed. The basic building blocks, including laser diode which is based on a rate equation model, external modulated transmitter, transmission fiber and receiver, are explained. The system comprises eight delay stages, has a maximum delay of 6.4μs with a 100ps step and operates over the 1-18 GHz band. This computer controlled prototype used low-cost commercially available components in conjunction with graded-index, single-mode fiber. Its overall performance is satisfied with the simulation result.

In order to analyze the rate of pressure drop of moist air in pipes, a new mathematical model of the friction pressure drop rate (FPDR) of slow transferring air was submitted in this paper. The parameters of the model are including air's characters of velocity, temperature, pressure, percentage of maximal relative humidity, and pipe's physical characters of length, diameter, equivalent roughness, the influences of which to the FPDR are analyzed and validated by simulations based on the model. We present the varying trends of FPDR, and the derivations of the maximal FPDR in laminar flow region and in onflow region. Then we have drawn a conclusion that the maximal FPDR lies in laminar flow region if there are both onflow region and laminar flow region. This study educes the measures to calculate the value of FPDR, and sums up the methods of reducing FPDR. This research may deliver references to optimize designs of liquid transferring in pipes.

An effective evaluation criterion is necessary to investigate the performance of a localization algorithm for wireless sensor networks. The Cramer-Rao Bound (CRB) is the lower bound of the localization error and can be applied as a performance evaluation criterion of a localization algorithm. The CRB on estimation accuracy for both range-based and range-free localization is studied. The CRB for range-based localization, which is suitable for different measurement methods, is derived on the basis of Gaussian noise model. For the range-free localization, the condition of CRB and the error distribution of the estimated distance which is computed by the average hop size and hop counter between nodes are analyzed. The result reveals that the condition is satisfied when the node location is calculated by the estimated distances. Subsequently the CRB for range-free localization is acquired. The localization accuracy of three typical algorithms, AHLos, DV-distance and DV-hop, are analyzed by the simulation experiments. The results verify the CRBs for both range-based and range-free localizations.

Wireless Sensor Networks (WSN) has been attracting growing interests for developing a new generation of large-scale embedded computing systems. However, the communication paradigms in wireless sensor networks differ from the ones associated to traditional wireless networks, triggering the need for new communication protocols and energy-consuming model. The NDSA (A Novel Data-sending Algorithm) Based on Cluster for wireless sensor networks aims at the design of a scalable data-sending model for supporting large-scale embedded computing applications with critical requirements. In this paper, we assume intra-cluster data taking on Gaussian distribution. According to the desired accuracy given by system, NDSA can automatically adjust the number of data-sending nodes. Experimental results show that NDSA can lengthen the life of network significantly better than other similar algorithms.

This paper discusses a new model that integrates the environment information for the robot path planning. This model could be regarded as a generalization of the artificial potential (AP) method. The path with the least turning angles, i.e. the smoothest, is defined as the optimal path. The finite element method is used to construct global optimum path planning strategy for a robot in a known environment for both static and dynamic cases. Simulation results show that this method is feasible for the path planning of a point robot in a complicated environment.

Signal transmission magnetic core is one of the key subassemblies for autonomous navigation sensor, realizeing the detection and transmission of the signal. In this research, finite element model of the magnetic core based on ANSYS was established, and the magnetic core was analyzed by method of lattice, with the magnetic fields computed by using magnetic vector potential (MVP). And then the total magnetic field distributions were determined and the simulation results were gained. Experiment results show that simulation signal of the model is consistent with the theoretical data. Additionally, the design of magnetic core could be optimized by the model and the research efficiency could be improved.