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Rolling bearing fault diagnosis method based on variational mode decomposition

A technology of variable mode decomposition and variational mode decomposition, applied in mechanical bearing testing, character and pattern recognition, testing of mechanical components, etc., can solve problems such as lack of theoretical basis, mode mixing, and inability to correctly separate components , to achieve the effect of suppressing spectrum noise and highlighting fault information

Inactive Publication Date: 2016-10-12
SHANDONG UNIV OF TECH
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  • Abstract
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Problems solved by technology

EMD belongs to recursive modal decomposition, and its disadvantages are: lack of theoretical basis; envelope estimation error is amplified by multiple recursive decompositions, prone to modal aliasing; there is an endpoint effect, which requires endpoint continuation; Components with similar frequencies are correctly separated

Method used

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  • Rolling bearing fault diagnosis method based on variational mode decomposition
  • Rolling bearing fault diagnosis method based on variational mode decomposition
  • Rolling bearing fault diagnosis method based on variational mode decomposition

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Embodiment Construction

[0049] The present invention will be further described below in conjunction with the accompanying drawings and implementation examples.

[0050] The hardware environment used for implementation is an ordinary computer, and the software environment is: Matlab R12 and Windows 8. We have realized the method that the present invention proposes with Matlab software. The analyzed signal comes from the bearing fault test bench. The original vibration signal is measured with a sampling frequency of 32768Hz through the acceleration sensor installed on the bearing seat. The rolling bearing model is MB ER-10K, and the speed is 2100 rpm (f r =35Hz).

[0051] refer to figure 1 , figure 1 It is an algorithm flowchart of the method of the present invention, and the specific implementation also needs to include the following steps:

[0052] (1) Obtain the vibration signal of the tested bearing through the acceleration sensor. Such as figure 2 shown;

[0053] (2) Use the predictiv...

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Abstract

The invention discloses a rolling bearing fault diagnosis method based on variational mode decomposition, which is used to analyze a rolling bearing fault based on a vibration signal. First, fault information enhancement processing is performed on a signal collected by a sensor using a predictive filtering method; then, variational mode decomposition is performed on the filtered signal to get four modes; next, a mode most relevant to a rolling bearing fault is selected according to a fault information index; and finally, an envelope autocorrelation spectrum analysis of the filtered signal is made, and fault characteristic frequency matching is performed to get fault information.

Description

technical field [0001] The invention relates to the field of mechanical fault diagnosis, and relates to the application of a vibration signal processing method in the field of rotating machinery fault diagnosis, in particular to a method for diagnosing rolling bearing faults by using predictive filtering and variable mode decomposition. Background technique [0002] Rolling bearings are commonly used support components in rotating machinery, and more than 30 percent of rotating machinery failures are related to bearing failures. The fault diagnosis technology of rolling bearings plays a vital role in monitoring the performance status of bearings and finding potential faults early. It can effectively improve the operation and management level of mechanical equipment and has significant economic benefits. [0003] Because in the actual fault diagnosis process, the fault signal is often accompanied by relatively large background noise, and even the signal may be covered by nois...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01M13/04G06K9/00
CPCG01M13/045G06F2218/06
Inventor 张丹隋文涛
Owner SHANDONG UNIV OF TECH
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