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Hub bearing fault diagnosis method

A fault diagnosis and wheel bearing technology, applied in the direction of mechanical bearing testing, etc., can solve problems such as difficulty in extracting wheel bearing faults

Active Publication Date: 2018-12-18
温州大学苍南研究院
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the difficulty of extracting wheel hub bearing faults in the background of strong noise, the inventor proposed a wheel hub bearing fault diagnosis method based on wavelet packet enhanced empirical mode decomposition, which can quickly and accurately diagnose the weak faults of wheel hub bearings

Method used

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Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0069] Example 1: Fault Diagnosis of Hub Bearing Outer Ring

[0070] Take an automobile hub bearing as SKF7018CD / P4A type, the pitch circle diameter is 115mm, the number of rolling elements is 20, the rolling element diameter is 12.5mm, and the contact angle is 15°. The sampling frequency is 20000Hz, the bearing runs without load, and the speed is 1200r / min. According to the calculation formula of the characteristic frequency of the bearing fault outer ring: The calculated outer ring fault characteristic frequency is 179Hz.

[0071] The time-domain diagram and the Hilbert envelope spectrum diagram of the original signal in the outer ring are as follows image 3 and Figure 4 As shown, due to the interference of strong background noise, Figure 4 The impact that matches the characteristic frequency of the outer ring fault cannot be found in the test, and the fault type cannot be judged. The db1 mother wavelet is used to decompose the original signal into 7 layers of wavel...

Embodiment 2

[0073] Example 2: Fault diagnosis of the inner ring of the hub bearing

[0074] Take an automobile hub bearing as SKF7018CD / P4A type, the pitch circle diameter is 115mm, the number of rolling elements is 20, the rolling element diameter is 12.5mm, and the contact angle is 15°. The sampling frequency is 20000Hz, the bearing runs without load, and the speed is 1200r / min. The formula for calculating the fault characteristic frequency of the bearing inner ring is: The calculated outer ring fault characteristic frequency is 220.9Hz.

[0075] The time-domain diagram and Hilbert envelope spectrum of the original signal in the inner circle are shown as Figure 8 and Figure 9 As shown, due to the interference of strong noise, Figure 9 The impact corresponding to the characteristic frequency of the inner ring fault cannot be found in the data, and the fault type cannot be judged. The db1 mother wavelet is selected to decompose the original signal into 7-layer wavelet packets. T...

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Abstract

The invention belongs to the field of automobile maintenance and relates to a wavelet packet enhanced EMD (Empirical Mode Decomposition) hub bearing fault diagnosis method. The method comprises the steps of firstly decomposing original signals by using wavelet packet decomposition to obtain sub-signals, and filtering away lowest frequency components in the sub-signals to reserve rest high-frequency components; adding the series of sub-signals to the original signals to enable the sub-signals to be distributed in the whole time-frequency space of the signals uniformly; then further decomposingthe mixed signals into multiple intrinsic mode functions by utilizing wavelet packet enhanced EMD and extracting components including high-fault characteristic information for reconstruction; and finally performing Hilbert envelope analysis on the reconstructed signals and diagnosing the bearing fault type. According to the wavelet packet enhanced EMD hub bearing fault diagnosis method, the original signals are subjected to fine decomposition and noise elimination by utilizing the wavelet packet decomposition and the signal-to-noise ratio is improved efficiently; the signals are further decomposed into local characteristic signals with different time scales by utilizing wavelet packet enhanced EMD, and the bearing fault type can be detected intuitively through envelope demodulation.

Description

technical field [0001] The invention relates to the field of automobile maintenance, in particular to a wheel hub bearing fault diagnosis method based on wavelet packet enhanced empirical mode decomposition. Background technique [0002] As a supporting rotating part, bearings are widely used in rotating machinery. There are no less than 50 sets of bearings installed in different rotating parts in a car. As a key component in the automobile suspension system, hub bearings are used to bear weight, reduce friction of the rotating pair, transmit torque, and provide precise guidance for the rotation of the hub, etc. Hub bearings operate at high speeds and simultaneously bear radial gravity loads, axial loads during steering and torque of the drive shaft. Therefore, the quality of the hub bearing directly affects the safety and comfort of the car when driving. In order to avoid safety problems caused by hub bearing failures, it is extremely important to detect and diagnose hub...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01M13/04
CPCG01M13/04
Inventor 向家伟王璐
Owner 温州大学苍南研究院
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