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Rolling bearing fault detection method based on vibration detection

A rolling bearing and vibration detection technology, applied in the direction of mechanical bearing testing, etc., can solve problems such as poor non-stationary signal processing effect, and achieve the effect of eliminating the interference of irrelevant information

Inactive Publication Date: 2013-05-01
KUNMING UNIV OF SCI & TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

Therefore, Fourier transform, conventional processing methods in the time domain and frequency domain, etc. have good effects on stationary signal processing, but the processing effect on non-stationary signals is not good.

Method used

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  • Rolling bearing fault detection method based on vibration detection
  • Rolling bearing fault detection method based on vibration detection
  • Rolling bearing fault detection method based on vibration detection

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0046] Embodiment 1: Diagnosis of Outer Ring Fault

[0047] In specific implementation, a kind of rolling bearing fault diagnosis method based on vibration detection is carried out according to the following steps:

[0048] Step (1), respectively install the acceleration sensors in the 3 o'clock direction of the motor bearing load area, use the data acquisition device integrated with the amplifier to collect the original vibration signal of the rolling bearing, and input the amplified and A / D converted vibration signal into the computer , where the sampling frequency is 12KHZ, and the original vibration signal of the rolling bearing with no load of the motor and a rotational speed of 1797RPM is obtained by sampling.

[0049] Step (2), such as figure 2 As shown, using the wavelet toolbox that comes with the MATLAB software in the computer to decompose the collected vibration signals into three layers of db1 wavelet packets;

[0050] Step (3), according to the energy calculat...

Embodiment 2

[0055] Example 2: Diagnosis of Inner Ring Faults

[0056] In specific implementation, a kind of rolling bearing fault diagnosis method based on vibration detection is carried out according to the following steps:

[0057] Step (1), respectively install the acceleration sensors in the 3 o'clock direction of the motor bearing load area, use the data acquisition device integrated with the amplifier to collect the original vibration signal of the rolling bearing, and input the amplified and A / D converted vibration signal into the computer , where the sampling frequency is 12KHZ, and the original vibration signal of the rolling bearing with no load of the motor and a rotational speed of 1797RPM is obtained by sampling.

[0058] Step (2), such as figure 2 As shown, using the wavelet toolbox that comes with the MATLAB software in the computer to decompose the collected vibration signals into three layers of db1 wavelet packets;

[0059] Step (3), according to the energy calculatio...

Embodiment 3

[0064] Example 3: Diagnosis of Rolling Element Faults

[0065] In specific implementation, a kind of rolling bearing fault diagnosis method based on vibration detection is carried out according to the following steps:

[0066] Step (1), respectively install the acceleration sensors in the 3 o'clock direction of the motor bearing load area, use the data acquisition device integrated with the amplifier to collect the original vibration signal of the rolling bearing, and input the amplified and A / D converted vibration signal into the computer . Among them, the sampling frequency is 12KHZ, and the original vibration signal of the rolling bearing with the motor no-load and the speed of 1797RPM is obtained by sampling.

[0067] Step (2), such as figure 2 As shown, using the wavelet toolbox that comes with the MATLAB software in the computer to decompose the collected vibration signals into three layers of db1 wavelet packets;

[0068] Step (3), according to the energy calculatio...

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Abstract

The invention relates to a fault diagnosis method, in particular to a rolling bearing fault diagnosis method based on the vibration detection. The method comprises the following steps of firstly decomposing the rolling bearing data collected by an acceleration sensor into three layers of wavelet packets, solving the energy of a third layer of wavelet packet coefficient rebuilding signals, selecting a frequency band with centralized energy to rebuild approximate evaluation of an original signal according to the variation of energy values of each frequency bands of the third layer; and utilizing a cepstrum to further analyze the rebuilt signal, and comparing the rebuilt signal with a theoretically-computed fault characteristic frequency and an edge frequency characteristic. By combining multiple resolutions of the wavelet packet and the cepstrum, the periodic component on a power spectrum, a separated-side frequency-band signal and the characteristics which are slightly subjected to the transmission route can be well detected. Meanwhile, the method is strong in manipulability and practicability.

Description

technical field [0001] The invention relates to a rolling bearing fault diagnosis method based on vibration detection, which belongs to the technical field of fault detection. Background technique [0002] Rolling bearings are very important parts in rotating machinery and also one of the fragile equipment. According to statistics, 30% of the failures of rotating machinery are caused by rolling bearing failures. When the equipment is running, wear, fatigue, corrosion, overload and other reasons may cause local damage to the rolling bearings. The defects of the rolling bearings will lead to severe vibration and vibration of the machine. Generate noise, and even cause serious accidents to the entire system. Therefore, the research on rolling bearing fault diagnosis is of great significance. [0003] Fault vibration signals of rolling bearings generally appear as complex non-stationary signals with aliasing of random and periodic pulses. In actual operation, local damage fau...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01M13/04
Inventor 吴建德马军张诗悦冷婷婷王晓东范玉刚黄国勇邹金慧邵宗凯张光辉
Owner KUNMING UNIV OF SCI & TECH
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