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7 September 2023 Fault diagnosis method of point machine based on vibration signal
Tongrui Yan, Jiazhen Zhang, Yongkui Sun
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Proceedings Volume 12790, Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023); 127901M (2023) https://doi.org/10.1117/12.2689779
Event: 8th International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023), 2023, Hangzhou, China
Abstract
Railway point machine is the key equipment to control the train path and change the operation direction. Considering the anti-interference characteristics of vibration signals, this paper innovatively proposes a fault diagnosis method for point machine based on vibration signal, which provides a new fault diagnosis method for point machine. Firstly, the vibration data of the point machine are preprocessed by using variational mode decomposition (VMD). Secondly, a hybrid feature extraction method is developed by combining various methods such as wavelet transform and frequency-domain feature extraction method, which can characterize the fault features more comprehensively. Finally, support vector machine (SVM) algorithm is used to judge fault conditions. The diagnosis accuracies of localization and inverse switching processes reach 100% and 98.9%, respectively. Comparative experiments indicate the superiority of the proposed method.
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Tongrui Yan, Jiazhen Zhang, and Yongkui Sun "Fault diagnosis method of point machine based on vibration signal", Proc. SPIE 12790, Eighth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2023), 127901M (7 September 2023); https://doi.org/10.1117/12.2689779
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KEYWORDS
Vibration
Feature extraction
Signal processing
Discrete wavelet transforms
Wavelet transforms
Particle swarm optimization
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