Dr. Kunpeng Feng Profile

Dr. Kunpeng Feng

at Harbin Institute of Technology

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Publications (4)

Proceedings Article | 7 March 2019 Paper

An interrogation method with high resolution and high response speed for FBGs-based sensors

Hong Dang, Kunpeng Feng, Xun Sun, Yihua Jin, Yizhao Niu, Tangjun Shi, Jiwen Cui, Jiubin Tan

Proceedings Volume 11053, 110531H (2019) https://doi.org/10.1117/12.2511221

KEYWORDS: Fiber Bragg gratings, Spectral resolution, Reflectivity, Sensors, Photodiodes, Environmental sensing, Mathematical modeling, Fabry–Perot interferometers, Optical communications, Dimensional metrology

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Recently, fiber Bragg gratings (FBGs) have played significant roles in a variety of fields such as optical communication, dimensional metrology, buildings health monitoring, ultrasonic waves and vibration measurement, petrochemical and other harsh/remote environments owing to their excellent performances like electromagnetic insensitivity, high accuracy and long term stability. In general, FBGs-based sensors are usually decoupled by detecting the variations of FBGs’ central wavelength, wherein, the accuracy and dynamic characteristics of the FBGs-based sensing are directly dependent on the spectral resolutions and response speed of the interrogation method. However, conventional spectral interrogation methods, which directly utilize an optical spectrum analyzer (OSA) with low resolutions and response speeds cannot satisfy the requirements of detecting small and dynamic variations of the FBGs’ central wavelength accurately. It is therefore of significance to find a FBGs interrogation method with high resolution and high response speed. In this paper, a high resolution and response speed interrogation method based on reflective-matched Fiber Bragg Gratings scheme is investigated in detail. The nonlinear problem of the reflective-matched FBGs sensing interrogation scheme is solved by establishing and optimizing the mathematical model. A mechanical adjustment to optimize the interrogation method by tuning the central wavelength of the reference FBG is investigated to improve the stability and antitemperature perturbation performance. To satisfy the measuring requirement of the optical and electric signal processing, an acquisition circuit board is well-designed, and experiments on the performance of the interrogation method are carried out. Experimental results indicate that the optical power resolution of the acquisition circuit border is better than 8 pW, and the stability of the interrogation method with the mechanical adjustment can reach 0.06%. Moreover, the linearity of the interrogation method is 3.3% in the measurable range of 60 pm; the influence of temperature is significantly reduced to 9.5%; the wavelength resolution and response speed can achieve 0.34 pm and 500 kHz, respectively.

Proceedings Article | 24 November 2016 Paper

Dimensional measurement of micro parts with high aspect ratio in HIT-UOI

Hong Dang, Jiwen Cui, Kunpeng Feng, Junying Li, Shiyuan Zhao, Haoran Zhang, Jiubin Tan

Proceedings Volume 10023, 100231J (2016) https://doi.org/10.1117/12.2243738

KEYWORDS: Fiber Bragg gratings, Optical fibers, Collimation, Precision measurement, Charge-coupled devices, Light sources, CCD cameras, Spherical lenses, CCD image sensors, Light

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Proceedings Article | 26 January 2016 Paper

Analysis and simulation method of the cantilever FBG sensors

Kunpeng Feng, Jiwen Cui, Xuelin Jiang, Junying Li, Jiubin Tan

Proceedings Volume 9903, 99031E (2016) https://doi.org/10.1117/12.2211919

KEYWORDS: Fiber Bragg gratings, Sensors, Analytical research, Fiber optics sensors, Performance modeling, Spherical lenses, Sensor performance, Optical fibers, Mechanics, Cladding

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Proceedings Article | 4 November 2014 Paper

An example image super-resolution algorithm based on modified k-means with hybrid particle swarm optimization

Kunpeng Feng, Tong Zhou, Jiwen Cui, Jiubin Tan

Proceedings Volume 9273, 92731I (2014) https://doi.org/10.1117/12.2073216

KEYWORDS: Reconstruction algorithms, Lawrencium, Image quality, Image processing, Image restoration, Particles, Particle swarm optimization, Image classification, Super resolution, Genetic algorithms

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