Research On The Fault Diagnosis Method For Bogie Bearings Of The Metro Vehicle

With the rapid development of urban rail transit in China, major capital cities are doing construction or planning their urban rail, and more attention is being paid to its operational safety. Bogie bearings form a critical component of metro vehicles, and their status is essential to the normal and safe operation of vehicles. Therefore, the train bogie bearing fault diagnosis has much practical significance. Developing intelligent online fault diagnosis schemes is an important issue worthy of study. Vibration signals contain a lot of information associated with faults. Based on wavelet packet-envelope analysis, this paper made an in-depth study on fault diagnosis method for bogie bearings.This paper introduces the typical structure of rolling bearings and fault forms, and studies the vibration mechanism of bogie bearings, and derives the fault characteristic frequency of rolling bearings. These are theoretical basis of fault diagnosis based on the vibration signal.Fault diagnosis includes fault feature extraction and fault pattern recognition. This paper combines wavelet packet decomposition and reconstruction and Hilbert transform to extract fault features effectively by obtaining the envelope spectrum of vibration signals in every frequency band. To address the deficiency of existing fault diagnosis methods, the paper puts forward a search algorithm for fault recognition. The search algorithm can imitate the human to "observe" the spectrum by computers, and makes effective pattern recognition through fault features extracted, and then has laid a solid foundation for intelligent fault diagnosis.In order to verify the effectiveness of the method, a test platform for bearing fault diagnosis was designed and built. Bogie bearings in three fault conditions used in Guangzhou Metro were tested on this platform, and results show that the method can accurately diagnose the bogie bearing failure.Finally, the paper designed an online fault diagnosis hardware device for subway train bogie bearings, and it was tested based on the proposed diagnostic method. The device can make accurate diagnosis for the three faults, predicting some usability.