Bearing fault self-diagnosis method and apparatus

Abstract

The invention discloses a bearing fault self-diagnosis method and device, which is to open a small groove on the bearing structure, and embed a wireless vibration micro-sensor module integrated with a fault diagnosis algorithm into the small groove on the bearing structure, through the wireless vibration micro The sensor module collects and processes bearing status signals online, and wirelessly outputs the analysis results to the remote monitoring PC at the receiving end. The present invention has the following characteristics: first, the wireless vibration micro-sensor module can be integrated with the bearing without changing the overall size of the bearing; second, it can collect and process the state signal of the bearing in real time and online; third, the collected state signal is controlled by Less pollution and more real; Fourth, the autonomy of the bearing fault diagnosis process is improved and the dependence on people is reduced.

Description

technical field [0001] The invention relates to online monitoring and diagnosis of bearing faults, and in particular provides an embedded self-diagnosis method and device for bearing faults. Background technique [0002] Bearings are an important class of rotating mechanical parts, which play a role in bearing and transmitting loads in mechanical equipment. Their operating status will directly affect the performance of the entire equipment, and once a failure occurs, it will often cause disastrous consequences. Therefore, real-time on-line monitoring of bearing status is of great significance and practical application value to improve its reliability and safety. [0003] The traditional bearing condition monitoring and fault diagnosis method is often realized by installing an acceleration sensor on the surface of its housing (such as a bearing housing) to measure and analyze vibration signals. It is related to the interface between the sensor and the connection between the ...

AI Technical Summary

Problems solved by technology

It is precisely because the sensor is in close contact with the shell structure rather than the rotating part itself, so the measured state signal is easily affected by the relevant structural vibration and environmental noise, which makes the signal-to-noise ratio of the fault feature signal low, which greatly increases the fault feature extraction. The difficulty of diagnosis is often unsatisfactory, and even misdiagnosis or missed diagnosis may occur.

On the other hand, in some practical applications, it is often difficult or even not allowed to install external sensors, making it difficult to obtain bearing status signals

Images