Vehicles Bearing Vibration Signal Analysis And Fault Diagnosis

The railway is a key of the national economy, it undertakes the national majority of transportation task, and the vehicles are means of delivery that complete these tasks. The bearing quality is one of important attributes affecting the railway transportation security. So it is of vital practical significance to study the fault diagnostic of locomotive vehicle bearing in order to avoid significant accidents, transform service system, promote economy development, and so on.This paper briefly introduces the mechanism analysis of locomotive vehicle bearing fault, including origin cause of formation of locomotive vehicle bearing fault, basic form, vibration mechanism, vibration model and fault characteristic frequency. Then it understands the current locomotive vehicle bearing fault monitor methods, And active fault diagnosis theory and methods at present of research field are studied which include diagnosis based parameters of time-frequency field, diagnosis based FFT, diagnosis based wavelet transform, diagnosis by Hilbert-Huang transform and some diagnosis based intelligent technology. Based on the methodology research the present paper combines and utilizes the methods of locomotive vehicle bearing fault diagnosis based on FFT transform, wavelet transform, Hilbert-Huang transform to process, analyse and compare vibration signal of locomotive vehicle bearing fault with the hand of parameters of time-frequency field nicely. Finally, the paper studies the applied technology including how to catch and modulate the signal of vibration acceleration, multithreading program, WIN32 API serial communication, DLL, OLE DB database program and complete the designing and debugging of software and hardware system.By processing and analyzing the data of the experiment on the wheelset rolling testbed, it is verified that the locomotive vehicle bearing fault diagnosis system can get the fault characteristic from the vibration acceleration signal under background of strong noise and identify the fault.The work of this paper is based on the vehicle wheelset testbed of a key laboratory we developed. The testbed is operated successfully in the laboratory.