Portable bearing fault diagnosis device and method based on vibration detection

Abstract

The invention provides a portable bearing fault diagnosis device and method based on vibration detection. The portable bearing fault diagnosis device comprises a vibrator sensor and a portable bearing fault diagnosis instrument, wherein the portable bearing fault diagnosis instrument comprises a shell and a circuit device; the circuit device comprises an A/D (Analogue/Digital) conversion module, a DSP (Digital Signal Processor) data analyzing module, an ARM (Advanced RISC Machines) data processing module, a storage module, a display module and a power supply module; the A/D conversion module is used for uploading an acquired and processed signal of a vibration sensor to the DSP data analyzing module for analysis and fault judgment; the ARM data processing module is used for receiving a processing result and distributing storage and display. The diagnosis method mainly comprises the following steps: a vibration signal is obtained by the vibration sensor; the signal is acquired by the A/D conversion module; the DSP data analyzing module is used for analyzing and processing; a fault analyzing result is stored and displayed. The portable bearing fault diagnosis device is simple and rapid to operate, and has high diagnosis precision and high automation degree; the real-time monitoring and the fault diagnosis of a rolling bearing fault can be effectively realized.

Description

technical field [0001] The invention relates to the technical field of bearing detection, in particular to a vibration detection-based portable rolling bearing fault diagnosis device and a diagnosis method thereof. Background technique [0002] Rolling bearings are important components of large-scale rotating equipment in coal mines. Due to their poor working environment and heavy loads, various failures are prone to occur during operation, which may even lead to equipment damage and safety accidents, affecting the safety of coal mine production. Therefore, it is very important to detect and diagnose the working state of rolling bearings. At present, the detection of rolling bearings in large-scale equipment in coal mines is generally carried out manually. The testing personnel judge the state of the rolling bearings by experience through manual testing or through the parameters or curves displayed on some auxiliary instruments. The quality requirements are high, the detect...

AI Technical Summary

Problems solved by technology

At present, the detection of rolling bearings in large-scale equipment in coal mines is generally carried out manually. The testing personnel judge the state of the rolling bearings by experience through manual testing or through the parameters or curves displayed on some auxiliary instruments. The quality requirements are high, the detection process is not intelligent enough, and the detection efficiency is low

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