Gearbox Fault Feature Extraction Method Based on Scale Space and Improved Sparse Representation

A scale space, sparse representation technology, applied in the testing of mechanical components, character and pattern recognition, and pattern recognition in signals, etc., can solve the problems of low time-frequency resolution and reconstruction accuracy, and eliminate modal aliasing. Phenomenon, accurate extraction, high-precision effects

Active Publication Date: 2022-05-24
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 with reference to the accompanying drawings.

[0050] This application discloses a method for extracting fault features of gearboxes based on scale space and improved sparse representation. figure 1 The flow chart shown includes the following steps:

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

[0052] Step 2: Use the scale space to divide the original signal into several frequency band component signals centered on the meshing frequencies of each order of the gear according to the frequency band, which specifically includes the following steps:

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

[0054]

[0055] In the formula, g(n; t) is a di...

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Abstract

The invention relates to a gear box fault feature extraction method based on scale space and improved sparse representation, comprising: using the scale space to divide the original signal into several frequency band component signals centered on the meshing frequency of each order of gears according to the frequency band; Signal construction of noise-free DCT dictionary; construction of observation dictionary for sparse decomposition of frequency band component signals, including adding noise signals to atoms of noise-free DCT dictionary in the iterative process of orthogonal matching pursuit algorithm based on singular value decomposition algorithm to obtain noise-containing DCT dictionary; select the optimal atom in the observation dictionary based on the fusion index of the minimum variance and inner product; use the observation dictionary to perform sparse reconstruction of the frequency band component signal based on the orthogonal matching pursuit algorithm; demodulate spectrum analysis and then extract the gearbox fault characteristic frequency. The invention is used to extract the fault features of the gearbox, and has higher time-frequency resolution and reconstruction accuracy than other methods.

Description

technical field [0001] The invention relates to the technical field of rotating machinery vibration signal analysis, in particular to a method for extracting fault features of gearboxes based on scale space and improved sparse representation. Background technique [0002] As one of the commonly used rotating machinery 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. Fault feature extraction is extremely complex and difficult. Therefore, how to effectively restore the fault characteristic information of gearboxes under str...

Claims

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Application Information

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Patent Type & Authority Patents(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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