Application of LCD-SVD Technique and CRO-SVM Method to Fault Diagnosis for Roller Bearing

Author:

Luo Songrong12,Cheng Junsheng2,Ao HungLinh345

Affiliation:

1. College of Mechanical Engineering, Hunan University of Arts and Science, Changde 415003, China

2. College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China

3. Institute for Computational Science, Ton Duc Thang University, Ho Chi Minh 70000, Vietnam

4. Faculty of Civil Engineering, Ton Duc Thang University, Ho Chi Minh 70000, Vietnam

5. Faculty of Mechanical Engineering, Industrial University of Ho Chi Minh City, Ho Chi Minh 70000, Vietnam

Abstract

Targeting the nonlinear and nonstationary characteristics of vibration signal from fault roller bearing and scarcity of fault samples, a novel method is presented and applied to roller bearing fault diagnosis in this paper. Firstly, the nonlinear and nonstationary vibration signal produced by local faults of roller bearing is decomposed into intrinsic scale components (ISCs) by using local characteristic-scale decomposition (LCD) method and initial feature vector matrices are obtained. Secondly, fault feature values are extracted by singular value decomposition (SVD) techniques to obtain singular values, while avoiding the selection of reconstruction parameters. Thirdly, a support vector machine (SVM) classifier based on Chemical Reaction Optimization (CRO) algorithm, called CRO-SVM method, is designed for classification of fault location. Lastly, the proposed method is validated by two experimental datasets. Experimental results show that the proposed method based LCD-SVD technique and CRO-SVM method have higher classification accuracy and shorter cost time than the comparative methods.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Mechanical Engineering,Mechanics of Materials,Geotechnical Engineering and Engineering Geology,Condensed Matter Physics,Civil and Structural Engineering

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