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Research on Information Fusion Fault Diagnosis System Based on Fuzzy Neural Network

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2 Author(s)
Fan Yang ; Sch. of Electr. & Inf. Eng., Wuhan Inst. of Technol., Wuhan ; Zhi Liao

For limitation of fault diagnosis methods in the engineering machine's hydraulic system, a fault diagnosis method based on multi-sensor information fusion was presented. This method simultaneously had the faculty that fuzzy theory could process uncertain or inaccurate information and the self-study capability of the neural network, which effectively enhanced the fault diagnosis's technical level collecting samples of data through establishing many sensors in the scene of the hydraulic system, and getting the membership of the fault through the membership function, then through the training of fuzzy neural network by the BP algorithm to achieve exact fault diagnosis function of hydraulic braking system. By contrast the diagnosis result of an example, it indicates that using multi-sensor information fusion as fault diagnosis method is more accurate and reliable than using single information as fault diagnosis method in the hydraulic system fault diagnosis.

Published in:

Computational Intelligence and Industrial Application, 2008. PACIIA '08. Pacific-Asia Workshop on  (Volume:2 )

Date of Conference:

19-20 Dec. 2008