Motor bearing fault diagnosis method and device based on signal enhancement and compression edge calculation

Abstract

The invention discloses a motor bearing fault diagnosis method and device based on signal enhancement and compression edge calculation. The method comprises the steps: (1) installing an acceleration sensor on a motor bearing pedestal to collect vibration signals; (2) performing demodulation, downsampling and signal enhancement on the acquired signals in an edge computing processor, performing compressed encoding on the processed data, transmitting the data to a wireless signal receiving module through a wireless signal transmitting module, and transmitting the data to a computer through an interface adapter; and (3) decoding the received data in a computer, and carrying out spectral analysis on the decoded signal to diagnose the bearing fault type. The method has the advantages that the data is compressed and enhanced by adopting edge calculation on the Internet of Things node, the signal-to-noise ratio of the output signal can be improved, the length of the signal needing to be sent is reduced, the sending time and power consumption are reduced, the bearing fault diagnosis efficiency is finally improved, and the service life of a battery of the Internet of Things node is prolonged.

Description

technical field [0001] The invention relates to the technical field of online diagnosis of motor bearing faults, in particular to a motor bearing fault diagnosis method and device based on signal enhancement and compression edge calculation. Background technique [0002] Motors are widely used in industrial production. Industrial motors are prone to performance degradation and mechanical and electrical failures after long-term operation. Studies have shown that 40%-50% of motor failures are caused by bearings, so it is of great significance to monitor the condition and diagnose faults of motor bearings. Vibration signal analysis is a common technology for motor fault diagnosis. The acceleration sensor installed on the motor bearing seat collects the motor vibration signal, and the signal processing and analysis can determine the fault type and fault severity of the motor bearing. [0003] Noise interference is the key core problem faced by motor bearing fault diagnosis. Th...

AI Technical Summary

Problems solved by technology

[0005] In recent years, the number of deployments of IoT devices has grown rapidly, and the resulting problem is that the transmission channel has become busy, and the computing and storage pressure of the data center has increased sharply.

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