Diagnosis method for fault position and performance degradation degree of rolling bearing

Abstract

The invention discloses a diagnosis method for the fault position and the performance degradation degree of a rolling bearing, belonging to the technical field of fault diagnosis for bearings, and solving the problems of low accuracy of diagnosis for fault position and performance degradation degree, and high time consumption of training existing in an intelligent diagnosis method for a rolling bearing in the prior art. A white noise criterion is added in the disclosed integrated empirical mode decomposition method, so that artificial determination for decomposition parameters can be avoided, and the decomposition efficiency can be increased; and via the disclosed nuclear parameter optimization method based on a hypersphere centre distance, the small and effective search region of nuclear parameters in a multi-classification condition can be determined, so that training time is reduced, and the final state hypersphere model of a classifier is given. The intelligent diagnosis method based on parameter-optimized integrated empirical mode decomposition and singular value decomposition, and combined with a nuclear parameter-optimized hypersphere multi-class support vector machine based on the hypersphere centre distance is higher in identification rate compared with the existing diagnosis method. The diagnosis method disclosed by the invention is mainly applied to intelligent diagnosis on the fault position and the performance degradation degree of the rolling bearing.

Description

technical field [0001] The invention relates to a method for diagnosing the fault location and performance degradation degree of a rolling bearing, and belongs to the technical field of bearing fault diagnosis. Background technique [0002] Rolling bearings are the key components of many rotating machines, and the degree of failure varies at different moments of operation. The existing rolling bearing fault diagnosis generally focuses on the determination of the fault location (inner ring, outer ring, rolling body). The performance degradation degree diagnosis is a new research direction recently proposed. A new expansion of technology. [0003] Recently, some performance degradation degree diagnosis methods have been proposed and received more and more attention. Scholars at the University of Wisconsin and the University of Michigan proposed performance degradation diagnostic methods based on cerebellar model neural networks, logistic regression, self-organizing feature m...

AI Technical Summary

Problems solved by technology

[0006] In order to solve the problem that the intelligent diagnosis method for rolling bearings in the prior art has a low diagnosis accuracy rate of fault location and performance degradation degree, and consumes a lot of training time, it further provides a rolling bearing fault location and performance degradation diagnosis method.

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