Rolling bearing fault diagnosis method based on vibration signal denoising and envelope analysis

Abstract

The invention discloses a rolling bearing fault diagnosis method based on vibration signal denoising and envelope analysis and belongs to the field of mechanical fault diagnosis and signal processing.The method comprises the following steps: firstly, performing primary collaborative filtering and denoising processing on four types of vibration signals of an outer ring fault, an inner ring fault,a rolling body fault and a normal condition of a rolling bearing, then performing primary collaborative filtering and denoising processing once again on the signals subjected to collaborative filtering and denoising, further removing noise interfering with fault diagnosis in the signals, afterwards, performing empirical mode decomposition (EMD) on the signals subjected to secondary collaborative filtering and denoising to obtain a plurality of implication mode functions (IMF), and selecting an IMF1 to carry out envelope analysis to judge the fault type of the rolling bearing. The result showsthat the vibration signals can be effectively denoised after being subjected to secondary collaborative filtering, then, envelope analysis based on empirical mode decomposition is carried out on the denoised vibration signals, and fault diagnosis can be accurately and effectively carried out.

Description

technical field [0001] The invention relates to a rolling bearing fault diagnosis method based on vibration signal denoising and envelope analysis, belonging to the field of mechanical fault diagnosis and signal processing. Background technique [0002] Rolling bearings are one of the most important parts of rotating equipment and other mechanical equipment, and its performance plays a decisive role in the operation of the entire equipment. However, the harsh working environment of rolling bearings makes it very likely to fail, so it is very important to diagnose the running state of rolling bearings in order to take timely measures for the normal operation of equipment. Therefore, the research on the diagnostic technology of rolling bearings is of great significance. [0003] Because the vibration signal contains most of the status information of the equipment during operation, and the vibration signal is easy to collect, the analysis of the vibration signal is one of the ...

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Problems solved by technology

Effectively solve the problem of difficult fault diagnosis caused by the influence of noise in the vibration signal

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