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Research on Fault Diagnosis Based on D-S Evidential Reasoning

机译:基于D-S证据推理的故障诊断研究

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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.
机译:针对传统诊断方法故障诊断准确性低的问题,提出了一种基于BP神经网络和基于D-S证据理论的多传感器信息融合技术的故障诊断方法,以实现故障诊断。在集成神经网络的基础上,引入证据推理,提出了一种结合神经网络和D-S证据推理的故障诊断技术(NN-DS诊断技术)。它分别从不同的症状领域使用BP神经网络局部诊断,并且每个网络接收到各自的结果,然后将D-S证据推理用于全局诊断以获得统一的结果。最后给出一个例子说明其有效性。

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