A scheme of omni-directional fault detection system for EMUs

Xinao Tao; Zhida Guo; Qian Li; Zhuo Li

doi:10.1117/12.2674631

28 April 2023 A scheme of omni-directional fault detection system for EMUs

Xinao Tao, Zhida Guo, Qian Li, Zhuo Li

Proceedings Volume 12626, International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022); 126261Q (2023) https://doi.org/10.1117/12.2674631
Event: International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022), 2022, Zhuhai, China

Abstract

This paper is mainly based on the artificial intelligence technology to automatically detect the visual inspection content of the top, bottom and both sides of the car body of the EMU. Specifically, image recognition is used to complete the fault identification and classification of the bottom, top and both sides of the car body of the EMU, and improve the detection efficiency. Specifically, the overall architecture of the omnidirectional fault detection system for multiple units is designed around the application of the maintenance operation process of the bottom, roof and both sides of the car body of the multiple units. The functional modules of the fault detection system for the bottom of the multiple units and the fault detection system for the roof and car body of the multiple units are analyzed and designed respectively, and the overall scheme design of the omni directional fault detection system for multiple units is completed.

Citation Download Citation

Xinao Tao, Zhida Guo, Qian Li, and Zhuo Li "A scheme of omni-directional fault detection system for EMUs", Proc. SPIE 12626, International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022), 126261Q (28 April 2023); https://doi.org/10.1117/12.2674631

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