Study Of Fault Diagnosis Of Rolling Bearings Based On The Wavelet Analysis

Rolling bearings are one of widely used mechanical parts in rotating machines and vulnerable to damage. Many faults of rotating mechanism are related to rolling bearings. The performance of roller bearings directly affects the performance of axis, gear and whole equipment. The defectiveness of rolling bearings can result in abnormal vibration and noise of equipment, even serious damage to the equipment and disaster. Thus, developing fault diagnosis of rolling bearings has great practical significance.This paper summarizes procreant cause of faults of rolling bearings in theory, constructs models of vary fault states. Vibration signal of rolling bearings is very complex, including not only moving information of bearings self but also many information of other related parts and structures. It is difficult if we only use time-domain or frequency-domain means to analyze vibration signal to find the before and after changes of faults .However, if time-frequency are provided at the same time, diagnostic veracity and reliability will be greatly improved. So we put forward and study a new fault diagnosis technique--time frequency diagnosis based on wavelet analysis.In order to diagnose the fault type precisely, the way of wavelet package multiple decomposition and recomposition is applied to extract fault character frequency of all parts of rolling bearings in this paper. According to the prosperity of wavelet package analysis, low frequency coefficients instead of signal growing tendency, we can approximately estimate whether the going state of rolling bearing is or not. We can also draw character frequency of every frequency segment, efficiently suppress noise and pioneer a new thought for extracting the faint signals from the strong background noise. By comparing the extracted character frequency with the fault character frequency of theoretical calculation, the fault is located precisely. Through processing and analysis of many data, the diagnosis result is satisfactory. It shows that wavelet package analysis can supply a convincing analysis means for rolling bearings fault diagnosis.