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| Rolling Bearing Fault Diagnosis Based on Local Characterist-scale Decomposition and Morphological Fractal Dimension |
| MENG Zong,LI Liang-liang |
| Key Laboratory of Measurement Technology and Instrumentation of Hebei Province, Yanshan University, Qinhuangdao, Hebei 066004,China |
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Abstract A rolling bearing fault diagnosis method based on the morphological fractal dimension and Local Characterist-scale Decomposition is proposed. Firstly, Local Characterist-scale Decomposition is used to decompose the mechanical fault signals into a set of Intrinsic scale components, and then the morphological fractal dimension of Intrinsic scale components which contain the Intrinsic scale component characteristics is calculated. This is obtained as a characteristic parameter to judge the signal fault types. The experimental results that the proposed method based on the morphological fractal dimension and Local Characterist-scale Decomposition can realize different signal states (inner fault, outer race fault, rolling element fault and normal) about the bearing fault and the rolling fault diagnosis effectively.
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Received: 11 July 2014
Published: 22 March 2016
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Corresponding Authors:
Zong MENG
E-mail: mzysu@ysu.edu.cn
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2016, Vol. 37 
