DocumentCode :
1754104
Title :
Research on Fault Diagnosis Based on D-S Evidential Reasoning
Author :
Na, Wang ; Yu, Liang ; He, Zhu
Author_Institution :
Sch. of Inf. Eng., Shenyang Univ. of Chem. Technol., Shenyang, China
Volume :
1
fYear :
2011
fDate :
28-29 March 2011
Firstpage :
692
Lastpage :
695
Abstract :
For the reasons of low fault diagnosis accuracy of traditional diagnosis methods, a fault diagnosis method fusing BP neural Network and multi-sensor information fusion technique based on D-S evidence theory was presented to realize fault diagnosis. On the base of integrated neural network, importing evidential reasoning, a fault diagnosis technique which combine neural network and D-S evidential reasoning (NN-DS diagnostic technique) is proposed. It uses BP neural network local diagnosis respectively from different symptom field, and each network receives respective result, then D-S evidential reasoning w ill be used for global diagnosis to gain a unified result. At last an exemple is given to indicate it´s validity.
Keywords :
backpropagation; case-based reasoning; fault diagnosis; neural nets; sensor fusion; BP neural Network; D-S evidence reasoning; fault diagnosis accuracy; multisensor information fusion; Accuracy; Artificial neural networks; Cognition; Fault diagnosis; Helium; Reliability theory; D-S evidence theory; fault diagnosis; multi-sensor information fusion; neural Network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2011 International Conference on
Conference_Location :
Shenzhen, Guangdong
Print_ISBN :
978-1-61284-289-9
Type :
conf
DOI :
10.1109/ICICTA.2011.180
Filename :
5750714
Link To Document :
بازگشت