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Reinforcement Method for Weak Faults of Rolling Bearings Based on Matrix Restoration

A matrix recovery and rolling bearing technology, applied in the testing of mechanical components, pattern recognition in signals, testing of machine/structural components, etc., can solve problems such as no solution algorithm, achieve enhanced fault characteristics, high calculation efficiency, and set parameters little effect

Active Publication Date: 2020-05-12
NORTHEASTERN UNIV LIAONING
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Problems solved by technology

Again, this is an NP-Hard problem for which there is no efficient algorithm for solving

Method used

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  • Reinforcement Method for Weak Faults of Rolling Bearings Based on Matrix Restoration
  • Reinforcement Method for Weak Faults of Rolling Bearings Based on Matrix Restoration
  • Reinforcement Method for Weak Faults of Rolling Bearings Based on Matrix Restoration

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Embodiment Construction

[0047] This embodiment proves the effectiveness of the method proposed in this patent by setting up simulation cases and experimental cases.

[0048] 1. Simulation case

[0049] In the simulation case, the bearing fault simulation signal is constructed by the following formula:

[0050]

[0051] In the formula: A m =0.9 is the maximum magnitude of the mth impact, β 1 =380 is the damping attenuation coefficient, ω n1 = 2048Hz is the assumed bearing fault frequency, T b Indicates the time interval between two adjacent impacts, δT indicates the error in the time interval between two adjacent impacts caused by slippage, and its value is 1-2%T b , μ(t) is the unit switching function. Assume that the bearing outer ring has a fault, the fault frequency is 125Hz, the signal sampling frequency is 20kHz, and the sampling time is 1s. The background noise interference is simulated by adding Gaussian white noise with a signal-to-noise ratio of -17db. The time-domain waveform of th...

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Abstract

The invention discloses a method for strengthening weak faults of rolling bearings based on matrix recovery, which belongs to the technical field of fault diagnosis of rotating machinery. By constructing the fault information matrix, the collected one-dimensional vibration signal is expressed in the form of a two-dimensional fault information matrix, so as to meet the input requirements of the matrix recovery theory, and use the matrix recovery algorithm to restore the shock characteristics from the two-dimensional fault information matrix. Based on the low-rank matrix, the cumulative average algorithm is used to restore the vibration signal without noise interference from the low-rank matrix. At the same time, considering the inevitable tail truncation phenomenon when constructing the fault information matrix, the positive sequence and reverse sequence fault information matrices are respectively constructed for the positive sequence and reverse sequence vibration signals, and the above three steps are carried out for the two fault information matrices respectively, and The denoising information obtained through the above two fault information matrices is synthesized to obtain a final denoising signal. The method is applicable to the analysis of vibration signals of rotating machinery in the field of fault diagnosis of rotating machinery.

Description

technical field [0001] The invention belongs to the technical field of fault diagnosis of rotating machinery, and relates to a method for strengthening weak faults of rolling bearings based on matrix restoration. Background technique [0002] Matrix recovery, first proposed by John Wright et al., also known as Robust PCA or sparse and low-rank matrix decomposition, means that when some elements of the matrix are severely damaged, the damaged elements are automatically identified and the original matrix is ​​restored. Similarly, it is assumed that the original matrix has a very good structure, that is, it is of low rank; in addition, it is assumed that only a few elements are severely damaged, that is, the noise is sparse but its size can be arbitrary. Then matrix recovery can be described by the following optimization problem: [0003] [0004] Among them, the objective function is the rank of the matrix L and the zero norm of the noise matrix S, that is, the number of n...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01M13/045G06K9/00
CPCG01M13/045G06F2218/04
Inventor 马辉俞昆付强曾劲
Owner NORTHEASTERN UNIV LIAONING
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