Diagnosis Technique Based on BP and D-S Theory

Qiu Yun Mo; Jie Cao; Feng Gao

doi:10.4028/www.scientific.net/AMR.179-180.544

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 179-180Diagnosis Technique Based on BP and D-S Theory

Diagnosis Technique Based on BP and D-S Theory

Abstract:

This paper constructs a common data fusion framework of fault diagnosis, by combining local neural networks with dempster-shafer (D-S) evidential theory. The RBF neural network is proposed as a local neural network of the fault pattern recognition, and its input vectors are extracted by the wavelet packet decomposition of various frequency energy. Then, the signal of each sensor separately has a feature level fusion. This method is effective, verified by experiments. The given decision level fusion is based on combining the features of the neural network and the D-S theory, and experiments show the results of the fault diagnosis are more accurate by this method.

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Periodical:

Advanced Materials Research (Volumes 179-180)

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544-548

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.179-180.544

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Online since:

January 2011

Authors:

Qiu Yun Mo, Jie Cao, Feng Gao

Keywords:

Data Fusion, D-S Theory, Fault Diagnosis, RBP Algorithm

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