Mechanical fault diagnosis method based on parameter adaptive VMD

Abstract

The invention relates to the field of mechanical vibration signal processing and fault diagnosis, and discloses a mechanical fault diagnosis method based on a parameter adaptive VMD. The signal detection capability of the VMD method in fault diagnosis is improved, and accurate mechanical fault diagnosis is realized. According to the invention, a weighted kurtosis index is used as a fitness function; a VMD decomposition parameter which best matches a signal to be analyzed is acquired through the self-adaption of an optimization algorithm; the optimal VMD decomposition parameter is used to carryout VMD decomposition on an original vibration signal; and mechanical fault feature extraction and fault diagnosis are realized. The method provided by the invention is suitable for mechanical faultdiagnosis.

Description

technical field [0001] The invention relates to the field of mechanical vibration signal processing and fault diagnosis, in particular to a mechanical fault diagnosis method based on parameter adaptive VMD. Background technique [0002] Once key mechanical equipment fails, it will bring huge economic losses and even casualties. Major accidents caused by mechanical equipment failures have occurred frequently at home and abroad. If the fault can be found in time during the operation of the equipment, it is of great significance to the safe operation of the equipment and the avoidance of economic losses and catastrophic accidents. [0003] An arduous task of mechanical fault diagnosis is how to extract useful fault feature information from complex monitoring signals, which has attracted extensive attention in the industry and academia in recent years. The variational mode decomposition (VMD) method is a signal adaptive decomposition method proposed by UCLA scholars Dragomirets...

AI Technical Summary

Problems solved by technology

However, the decomposition parameters of the VMD method (the number of modal components and the frequency bandwidth control parameters of the modal components) have a significant impact on its decomposition results

At present, in the field of mechanical failure, the VMD decomposition parameters are specified in advance in most studies, and it is difficult to obtain satisfactory analysis results.

Although a few scholars have proposed to use the envelope entropy as a fitness function to optimize the VMD decomposition parameters, the adopted envelope entropy only considers the characteristics of the decomposed modal components, and does not consider the correlation between the modal components and the original signal, which is easy to cause missing information problem

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