A Rolling Bearing Fault Detection Method Based on Acoustic Vibration Signal Fusion

Abstract

The invention provides a rolling bearing fault detection method based on acoustic vibration signal fusion. Firstly, the vibration signal and acoustic signal of the rolling bearing to be tested are extracted, and then the sliding rectangular window function of the acoustic signal is established. Secondly, starting from the first signal point of the vibration signal to be detected, the fusion signal after each movement is established by moving the rectangular window, and Solve the root mean square value and mean soft value of the fusion signal to obtain the average slip value, find the optimal fusion signal, and finally diagnose the fault of the bearing to be tested by judging the value range of the approximate fault characteristic frequency where the optimal fusion signal is located; The invention solves the problems of limited vibration sensor layout and low amplitude at the fault characteristic frequency; it also solves the problem of low signal-to-noise ratio caused by the influence of background noise on acoustic signals, and can accurately identify weak faults of rolling bearings, improving The accuracy and efficiency of diagnosis are improved, and good results have been achieved in rolling bearing condition monitoring.

Description

technical field [0001] The invention relates to the technical field of bearing fault diagnosis, in particular to a rolling bearing fault detection method based on acoustic vibration signal fusion. Background technique [0002] Rolling bearings are one of the most widely used components in rotating machinery, and are widely used in important fields such as machining, metallurgy, chemical industry and aviation. Because rolling bearings are often in high-temperature, high-speed and heavy-load working environments, rolling bearings are easily damaged. Once they fail and are not detected in time, it will cause machine failure and unexpected shutdown, resulting in huge economic losses and even threats. to the personal safety of workers. Therefore, in rotating machinery, fault diagnosis of rolling bearings plays a vital role. [0003] The vibration signals of rolling bearings contain a lot of information and are easy to obtain. They have been widely used in the fault diagnosis of...

AI Technical Summary

Problems solved by technology

However, the vibration signal is obtained through contact measurement, and the layout of the vibration sensor is limited by the environment, so it is not suitable for installation in a working environment with high temperature, high humidity and high corrosion, and the amplitude of the fault frequency is low, so it is difficult to detect weak faults , and the acoustic signal is obtained through non-contact measurement, which can improve the limitation of contact measurement of vibration signal, and has become a new research method in fault diagnosis

However, in the process of collecting acoustic signals, fault feature information is easily affected by background noise, resulting in low signal-to-noise ratio and insufficient diagnostic accuracy.

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