High-speed rolling bearing fault diagnosing method based on time domain and frequency domain state monitoring

Abstract

A high-speed rolling bearing fault diagnosing method based on time domain and frequency domain state monitoring includes the steps of firstly, acquiring the vibrating signal of a faultless bearing, and calculating the dimension / dimensionless parameters of the vibrating signal after performing noise reduction on the vibrating signal; secondly, acquiring the vibrating signal of a bearing at a to-be-diagnosed moment, calculating the dimension / dimensionless parameters of the vibrating signal after performing noise reduction on the vibrating signal, and comparing the dimension / dimensionless parameters with the faultless dimension / dimensionless parameters; thirdly, calculating the percentages of the diagnosing moment parameters and the faultless moment parameters so as to achieve bearing state online monitoring based on the time domain; fourthly, acquiring the type and size information of the bearing and calculating the BPFI, BPFO, BSF and FTF of the bearing; fifthly, band-pass filtering; sixthly, using Hilbert transformation to acquire the envelope signal of the vibrating signal after band-pass filtering; seventhly, performing FFT analysis on the envelope signal and acquiring envelope spectrum; eighthly, searching the first 15 maximum values through maximum value searching, and comparing the maximum values with bearing fault feature frequencies and rotation frequencies; ninthly, performing faultless judging and positioning according to the comparison result.

Description

technical field [0001] The invention relates to a fault diagnosis method for rolling bearings, in particular to a fault diagnosis method for high-speed rolling bearings based on time domain and frequency domain state monitoring. Background technique [0002] High-speed rolling bearings are widely used in rotating machinery and equipment. Although its manufacturing tolerance requirements are very strict, due to the fact that the bearings are often subjected to a large dynamic load during operation, coupled with frequent improper lubrication, dust pollution, moisture corrosion, and scratches during installation, only 10% Up to 20% of bearings reach their design life. Bearing failure will lead to abnormal operation of the whole machine, and serious bearing failure may even cause the failure of the whole machine, resulting in high maintenance costs. Therefore, bearing condition monitoring occupies an extremely important position in the field of preventive maintenance of rotati...

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Problems solved by technology

[0003] Time-domain diagnosis is a fast but rough diagnosis method, which can judge whether there is a fault in high-speed rolling bearings and determine the severity of the fault according to a given threshold. However, because macroscopic statistics are used as fault symptoms, further fault location cannot be performed.

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