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Bearing fault diagnosis method based on homogeneous phase empirical mode decomposition and fast spectral kurtosis

A technology of empirical mode decomposition and fault diagnosis, which is applied in the direction of mechanical bearing testing, pattern recognition in signals, character and pattern recognition, etc., and can solve problems such as empirical mode decomposition and modal aliasing

Active Publication Date: 2020-03-20
ANHUI UNIVERSITY OF TECHNOLOGY
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Problems solved by technology

However, the empirical mode decomposition has serious problems such as mode aliasing

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  • Bearing fault diagnosis method based on homogeneous phase empirical mode decomposition and fast spectral kurtosis
  • Bearing fault diagnosis method based on homogeneous phase empirical mode decomposition and fast spectral kurtosis
  • Bearing fault diagnosis method based on homogeneous phase empirical mode decomposition and fast spectral kurtosis

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Embodiment Construction

[0043] The specific steps of a bearing fault diagnosis method based on uniform phase empirical mode decomposition and fast spectral kurtosis provided by the present invention are as follows:

[0044] (1) Decompose the bearing fault signal by adopting the homogeneous phase empirical mode decomposition method;

[0045] (2) Calculate the kurtosis of all components decomposed, and select the component with the largest kurtosis;

[0046] (3) Use fast spectral kurtosis to process the component with the largest kurtosis to obtain the power spectrum with the best analysis frequency band;

[0047] (4) Analyzing the power spectrum to identify the fault feature of the bearing fault signal.

[0048] In the embodiment of the present invention, a rolling bearing is used as a fault object to illustrate the effectiveness of the method, and the fault signal of the outer ring rolling bearing is analyzed.

[0049] The experimental verification uses the test bearing data of the Western Reserve ...

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Abstract

The invention discloses a rolling bearing fault diagnosis method based on homogeneous phase empirical mode decomposition and fast spectral kurtosis, and belongs to the technical field of mechanical fault diagnosis. The method comprises the following steps: decomposing a bearing fault signal by adopting a homogeneous phase empirical mode decomposition method; calculating kurtosis of all decomposedcomponents, and selecting the component with the maximum kurtosis; processing the maximum kurtosis component by using the fast spectral kurtosis to obtain an optimal analysis frequency band; and performing power spectrum analysis, and identifying rolling bearing fault characteristics. According to the method disclosed by the invention, the homogeneous phase empirical mode decomposition and the fast spectral kurtosis are combined, so that not only can the fault characteristics of the rolling bearing be effectively identified, but also the method has advantages in the aspect of suppressing interference signals.

Description

Technical field: [0001] The invention belongs to the technical field of mechanical fault diagnosis, and in particular relates to a bearing fault diagnosis method based on homogeneous phase empirical mode decomposition and fast spectrum kurtosis. Background technique: [0002] Rolling bearings are one of the most commonly used and easily damaged parts in rotating machinery. Therefore, it is of great significance to carry out research on fault diagnosis of rolling bearings. Fault signals of rolling bearings are often nonlinear and non-stationary, and traditional signal processing methods are difficult to obtain satisfactory results. Empirical mode decomposition method, as an adaptive signal processing method, can effectively deal with nonlinear and non-stationary signals, so it is used in the field of bearing fault diagnosis. However, the empirical mode decomposition has serious problems such as mode aliasing. The homogeneous phase empirical mode decomposition is improved on...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G01M13/04
CPCG01M13/04G06F2218/02G06F2218/08
Inventor 郑近德丁克勤刘庆运苏缪涎潘海洋童靳于
Owner ANHUI UNIVERSITY OF TECHNOLOGY
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