Fault diagnosis based on integrated neural network and D-S evidential reasoning

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 example is given to indicate it´s validity.