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Automobile hub bearing fault feature extraction method based on optimal quality factor selection

A technology of automobile hub and fault features, which is applied in the field of fault feature extraction of automobile hub bearings, and can solve the problem of large random selection of quality factors

Active Publication Date: 2018-12-28
江阴智产汇知识产权运营有限公司
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AI Technical Summary

Problems solved by technology

[0004] Aiming at the problem that the quality factor selection of the existing resonance sparse decomposition is arbitrarily large, the present invention proposes an automobile hub bearing fault feature extraction method based on the selection of the best quality factor of the resonance sparse decomposition, and selects the best quality factor of the resonance sparse decomposition through a successive optimization algorithm Quality factor, and then effectively decompose the low resonance component with transient impact component signal and high resonance component with harmonic component, and realize the feature extraction of automobile hub bearing fault based on the best quality factor

Method used

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  • Automobile hub bearing fault feature extraction method based on optimal quality factor selection
  • Automobile hub bearing fault feature extraction method based on optimal quality factor selection
  • Automobile hub bearing fault feature extraction method based on optimal quality factor selection

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Embodiment

[0076] First, select the automobile wheel bearing shown in Table 1. Then, cut a groove with a width of 0.3 mm and a depth of 0.05 mm in the outer ring of the bearing. Finally, install the acceleration sensor on the bearing seat to obtain the vibration signal x in the vertical direction.

[0077] Table 1 Parameters of wheel hub bearings

[0078] .

[0079] Step 1: The information collection module collects the vibration signal x of the automobile hub bearing through the acceleration sensor, the waveform is as Figure 4 Shown. Sampling frequency f s It is 100kHz, the sampling time t is 0.5s, and the number of sampling points N is 50000.

[0080] Step 2: The resonance sparse decomposition parameter initialization module sets the initial resonance sparse decomposition parameter Q h = 3, r h = 3, J h = 30; Q l = 1, r h = 3, J l = 11.

[0081] Step 3: The quality factor is optimized successively for high and low quality factors Q h And Q l Optimize and find the best quality factor as Q h ...

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Abstract

The invention discloses an automobile hub bearing fault feature extraction method based on optimal quality factor selection. Firstly, a vibration signal is collected; then resonance sparse decomposition parameters are initialized; by utilizing a progressive optimization algorithm, an optimal quality factor is obtained by taking an RSK index as a target function; and finally, envelope analysis is performed for a low-resonance component obtained by carrying out resonance sparse decomposition on the signal under the optimal quality factor to obtain an envelope spectrum, so that fault features canbe effectively extracted. According to the method, the problems of high randomness, uncertainty and difficulty in obtaining an ideal decomposition effect due to manual selection of the quality factorin a traditional resonance sparse decomposition method are avoided; the optimal quality factor can be selected in a self-adaptive mode; and the fault features of an automobile hub bearing under intermittent strong-interference noises can be effectively extracted.

Description

Technical field [0001] The invention belongs to the field of automobile wheel bearing fault diagnosis, and more specifically relates to an automobile wheel bearing fault feature extraction method based on the selection of the best quality factor of resonance sparse decomposition. Background technique [0002] Automobile wheel bearing is one of the important parts of automobile transmission and load bearing. It bears both axial load and radial load. Its performance will directly affect the safety of automobile driving and the comfort of passengers. Due to the complex and changeable driving conditions of automobiles, wheel bearings are often in a working environment with high loads and frequent shifts and loads. It is easy to induce mechanical failures such as local wear and tear, which can lead to damage to the hub. In severe cases, it may cause the car to occur on the road. Out of control. The main cause of hub bearing failure is the damage of the inner ring, outer ring and roll...

Claims

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Application Information

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IPC IPC(8): G01M13/04G06K9/00
CPCG01M13/045G06F2218/08
Inventor 李仲兴周庄薛红涛江洪
Owner 江阴智产汇知识产权运营有限公司
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