Three-layer information fusion for braking system fault diagnosis

In this paper, information fusion fault diagnosis technology was applied to a hoist system, and three-layer information fusion fault diagnosis was proposed. Compared with the principal component analysis of fault diagnosis and the two-layer information fusion, the results indicate that Elman neural...

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Bibliographic Details
Published in2012 5th International Conference on Biomedical Engineering and Informatics pp. 1580 - 1584
Main Authors Shaojin Wang, Jian Wang, Zhaojian Yang, Gaofeng Song
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2012
Subjects
braking system
fault diagnosis
feature extraction
information fusion
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Summary:In this paper, information fusion fault diagnosis technology was applied to a hoist system, and three-layer information fusion fault diagnosis was proposed. Compared with the principal component analysis of fault diagnosis and the two-layer information fusion, the results indicate that Elman neural network has ability with higher accuracy classification and better stability than Error Back Propagation (RBF) Neural Network in small training sample. If more evidence exist, Dempster Shafer (DS) fusion method will be more practical than Yager fusion method. Experiment verified the feasibility of this method. It will improve the accuracy of diagnosis system, and provide greater reliability for coal mine safety production.
ISBN:9781467311830
1467311839
DOI:10.1109/BMEI.2012.6513114