【摘要】 根据模糊神经网络和专家系统的特点,建立了模糊神经网络与专家系统相结合的汽轮发电机组故障诊断系统。系统采用模糊隶属度函数表示难以准确描述的领域专家知识;推理过程中,采用神经网络进行前向推理,并参考神经网络的输出,用专家系统进行反向推理,结合了神经网络求解迅速和专家系统解释清晰的优点,并提高了系统诊断能力;最后,采用信息融合方法处理冗余的诊断结果,提高了系统的综合诊断性能。更多还原

【Abstract】 A fault diagnosis system based on integration of fuzzy neural network and expert system is developed for turbine-generator units. Fuzzy membership functions are used to deal with the uncertainty or indistinction of the faults and rules knowledge. Neural network is used for forward reasoning and expert system is used for backward reasoning, with referencing the results of the neural network. The cooperation of the two means can lead to fast calculation, plain explanation and good diagnosis ability. The diagnosis results are synthesized by information fusion method to improve the performance of the system.更多还原