VR and AR are new computer technologies for creating simulated environments in the field of the shipping industry. Therefore, it is of great significance to study the application of VR and AR by 5G enabled technology with large bandwidth and low delay in ship assembly. An application framework of the digital assembly system of a marine turbocharger based on VR/AR is presented and its operation mechanism is analyzed in his paper. The application framework of the digital assembly system of turbochargers based on VR/AR mainly consists of five parts: the physical layer, data layer, system underlying layer, system layer, and application layer. System design and implementation and implementation effect of the digital assembly system of the marine turbocharger based on VR/AR are described in detail. The operation mode of the digital assembly simulation system of a turbocharger based on VR/AR is studied to improve the production capacity of turbochargers assembly.
Rolling bearing is an important part of rotating machinery. On-line condition monitoring and fault diagnosis of rolling
bearing are of great significance to ensure the stable operation of rotating machinery. In this paper, a novel rolling
bearing fault diagnosis method is proposed based on continuous wavelet transform (CWT) and transfer convolutional
neural network. Firstly, the vibration signal is converted into time-frequency image through CWT. Then, on the basis of
the pre-trained convolutional neural network model, the construction of rolling bearing fault diagnosis model is
conducted based on transfer learning. Moreover, an open source data set obtained from the Bearing Data Center of Case
Western Reserve University was used to verify the effectiveness of the proposed method. Finally, the comparative
analyses were conducted among the proposed method and other rolling bearing fault diagnosis method. The results show
that the proposed method can achieve higher accuracy on the accurate rolling bearing diagnosis of fault modes and fault
degrees.
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