Abstract
To identify and diagnose the latent leakage faults of key pneumatic units in the Chinese standard Electric Multiple Units (EMU) braking system, a multi-source information fusion method based on Kalman filtering, sequential probability ratio test (SPRT), and support vector machine (SVM) is proposed. The relay valve is taken as an example for research. Firstly, Kalman’s state estimation function is used to obtain the innovation sequence, and the innovation sequence is input into the SPRT model to help recognize latent leakage faults of the relay valve. Using this method, the problem of the incomplete training set of the traditional SPRT method due to the change of the braking level and the vehicle load is solved. Secondly, the eight time-domain parameters of the relay valve input and the output pressure signal are extracted as fault characteristics, and then input to the support vector machine to realize the internal and external leakage fault diagnosis of the relay valve, which provides a reference for maintenance. Finally, this method is verified by the fault simulation data by quickly identifying latent leakage faults and diagnosing the internal and external leakage at a fault recognition rate of 100% by SVM under small sample conditions.
Highlights
IntroductionEnergy-savings, speed, and comfort are favored by passengers of the “Fuxing” Chinese Standard
Energy-savings, speed, and comfort are favored by passengers of the “Fuxing” Chinese StandardElectric Multiple Units (EMU)
The multi-source information fusion method of the Kalman filter, sequential probability ratio test (SPRT), and support vector machine (SVM) is proposed to be applied to the standard EMU for identifying and diagnosing latent leakage faults in the critical pneumatic units of the brake system
Summary
Energy-savings, speed, and comfort are favored by passengers of the “Fuxing” Chinese Standard. During long-term operation, leakage faults may occur due to the wear of rubber seals, spring fatigue, and mechanical jams caused by grease failure These faults may degrade the performance of the pneumatic unit and even cause functional failures, such as the brakes not releasing or providing insufficient braking power, all of which can affect operational safety and efficiency [4,5,6,7,8,9]. The multi-source information fusion method of the Kalman filter, SPRT, and SVM is proposed to be applied to the standard EMU for identifying and diagnosing latent leakage faults in the critical pneumatic units of the brake system. Considering the limited number of relay valve faults and the research of the leakage mechanism of the relay valve, the leakage fault simulation test is carried out to obtain the fault sample data and to verify the feasibility of the method
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