Gearbox fault feature extraction method based on scale space and improved sparse representation

A technology of scale space and sparse representation, which is applied in character and pattern recognition, testing of mechanical components, pattern recognition in signals, etc. It can solve the problems of low time-frequency resolution and reconstruction accuracy, and eliminate modal aliasing phenomenon, good time-frequency characteristics, and the effect of accurate extraction

Active Publication Date: 2021-08-27
SOUTHEAST UNIV
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Problems solved by technology

[0005] Aiming at the defects of the prior art, the present invention proposes a gearbox fault feature extraction method based on scale space and improved sparse representation to solve the problems of low time-frequency resolution and reconstruction accuracy

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  • Gearbox fault feature extraction method based on scale space and improved sparse representation
  • Gearbox fault feature extraction method based on scale space and improved sparse representation
  • Gearbox fault feature extraction method based on scale space and improved sparse representation

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Embodiment Construction

[0049] The specific embodiments of the present invention will be described below in conjunction with the accompanying drawings.

[0050] This application discloses a gearbox fault feature extraction method based on scale space and improved sparse representation, refer to figure 1 The flowchart shown includes the following steps:

[0051] Step 1. Obtain the original vibration signal of the gearbox that needs to be decomposed;

[0052] Step 2. Divide the original signal into a number of frequency band component signals centered on the meshing frequency of each order of the gears according to the frequency bands using the scale space, specifically including the following steps:

[0053] 2.1) Find the frequency spectrum f of the original signal x(t) of the gearbox vibration, regard the frequency spectrum f as a set of histograms, and use the Gaussian kernel function to perform circular convolution on the frequency spectrum f, the formula is as follows:

[0054]

[0055] In th...

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Abstract

The invention relates to a gearbox fault feature extraction method based on a scale space and improved sparse representation. The method comprises the following steps: dividing an original signal into a plurality of frequency band component signals by using a scale space according to a frequency band, wherein the frequency band component signals take the meshing frequency of each order of a gear as a center; constructing a noiseless DCT dictionary for the frequency band component signals; constructing an observation dictionary used for performing sparse decomposition on the frequency band component signals, including adding noise signals into atoms of a noiseless DCT dictionary in an orthogonal matching pursuit algorithm iteration process based on a singular value decomposition algorithm to obtain a noisy DCT dictionary; selecting an optimal atom in the observation dictionary by taking a fusion index of the minimum variance and the inner product as a criterion; based on an orthogonal matching pursuit algorithm, using the observation dictionary to carry out sparse reconstruction on the frequency band component signals; and analyzing the demodulation spectrum and then extracting the fault characteristic frequency of the gearbox. The method is used for extracting the fault features of the gearbox, and has higher time-frequency resolution and reconstruction precision compared with other methods.

Description

technical field [0001] The invention relates to the technical field of vibration signal analysis of rotating machinery, in particular to a gear box fault feature extraction method based on scale space and improved sparse representation. Background technique [0002] As one of the commonly used rotating machines in industrial scenes, the gearbox has a fixed transmission ratio, large driving torque and compact structure, and has been widely used in various machinery. Gearboxes usually work under harsh conditions and are prone to failures, so the research on fault diagnosis of gearboxes has important practical significance. However, the vibration signal measured in actual engineering is always nonlinear and non-stationary, which is affected by the coupling effect of multiple transmission paths between components. The vibration signal is doped with strong background noise and interference source signals, resulting in the gear box Fault feature extraction is extremely complex an...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01M13/021G01M13/028G06K9/00
CPCG01M13/021G01M13/028G06F2218/04G06F2218/12
Inventor 毛一帆许飞云胡建中贾民平黄鹏
Owner SOUTHEAST UNIV
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