A Fault Diagnosis Method for Single Pitting Corrosion of Rotating Machinery Bearing Based on Wavelet Analysis

摘要

Single pitting corrosion is a type of failure that often occurs in rotating machinery bearings, which seriously interferes with the normal operation of rotating machinery bearings. Therefore, a fault diagnosis method based on wavelet analysis for single pitting corrosion of rotating machinery bearings is proposed. Acquire vibration signals of rotating machinery bearings, use wavelet analysis to denoise the collected signals, extract fault features through empirical mode decomposition (EMD), and use BP neural network algorithm to perform fault classification and identification based on the extraction results to realize rotating machinery bearings Single point pitting fault diagnosis. The simulation results show that, compared with the envelope demodulation analysis method, the research method has higher accuracy and faster diagnosis efficiency for single pitting corrosion of rotating machinery bearings, which confirms its application value.