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Mechanical vibration source number estimating method in underdetermined blind separation

An underdetermined blind separation and mechanical technology, which is applied in the field of mechanical vibration source number estimation, can solve the problem that the source number estimation problem is not considered, and achieve the effect of accurate vibration source number.

Inactive Publication Date: 2017-05-31
NANCHANG HANGKONG UNIVERSITY
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Problems solved by technology

However, the above algorithm is only applicable under overdetermined or rated mixed conditions, that is, when the number of observed signals is greater than or equal to the number of source signals
However, the problem of source number estimation when the number of observed signals is smaller than the number of source signals is not considered

Method used

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  • Mechanical vibration source number estimating method in underdetermined blind separation
  • Mechanical vibration source number estimating method in underdetermined blind separation
  • Mechanical vibration source number estimating method in underdetermined blind separation

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Embodiment Construction

[0033] The present invention will be further described below in conjunction with accompanying drawing, implementation principle, simulation and engineering application example, see Figure 1 to Figure 13 .

[0034] 1. Theoretical basis of parallel factor analysis:

[0035] parallel factor model [11] It is a multi-dimensional matrix low-rank decomposition model, also known as trilinear model, its model is as follows figure 1 shown. Three-dimensional matrix X ∈ C I×J×N The scalar form of the PARAFAC decomposition can be expressed as:

[0036]

[0037] Where: i=1,2,...,I, j=1,2,...,J, n=1,2,...,N, m=1,2,...,M; A∈C I×M , B∈C J ×M and C∈C N×M are the three carrying matrices of the model; E∈C I×J×N is the noise matrix. Trilinear models can also be written in slice form:

[0038]

[0039] Where: D i (A) is a diagonal matrix composed of elements in row i of matrix A. Different from low-rank decomposition of two-dimensional matrix, PARAFAC model decomposition is uni...

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Abstract

The invention discloses a mechanical vibration source number estimating method in an underdetermined blind separation; the method includes steps of applying a second-order non-stable source separation, separating the centralized sensor data to nonoverlapping data blocks; calculating a single time delay covariance matrix of every data block and overlapping to be three-order tensor or a parallel factor model; then applying a nuclear consistent diagnosis algorithm and estimating the best component number of the parallel factor model, and thereby acquiring the vibration source number of a mechanical system. Compared with the existed mechanical vibration source number estimating method, the presented method can effectively solve the vibration source number estimation problem under the underdetermined blind separation, and has wide application prospect in multi-fault composite diagnosis.

Description

technical field [0001] The invention relates to a multi-fault compound diagnosis technology for mechanical equipment, in particular to a method for estimating the number of mechanical vibration sources in underdetermined blind separation. Background technique [0002] Multi-fault compound diagnosis is a difficult point in mechanical fault diagnosis. Although compound faults are related to individual faults, the various manifestations of vibration are different. Compound faults are not simply a superposition of single faults. The faults are mutual. Affected, resulting in richer vibration patterns. In engineering practice, if various fault signals can be separated, it can be easily diagnosed according to the vibration characteristics of various faults. The blind source separation technology that emerged in the 1990s provides a new way of thinking for the concurrent diagnosis of multiple mechanical faults. The basic meaning of blind source separation refers to a technique for...

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Application Information

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IPC IPC(8): G01M13/02G01R31/34
CPCG01M13/028G01R31/34
Inventor 李志农杨诚袁瑾章熙琴
Owner NANCHANG HANGKONG UNIVERSITY
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