基于信息熵的系统诊断参数交互推理选择方法

Information Entropy Based System's Diagnostic Parameter Choosing Method with Backward and Forward Reasoning

  • 摘要: 介绍了一种多输入、多输出系统的故障诊断参数选择方法,该方法以可观参数集的信息熵为标准,进行启发性诊断参数集的划分,先以系统状态决定的启发性诊断多数子集作为驱动数据,实施正向推理,缩小目标集合;再以故障目标集合为对象,进行反向推理以确定最终故障集合;最后将故障集合的元素所对应的可测诊断参数作为系统的诊断参数进行测量。该方法构成了诊断型专家系统的一子部分。

     

    Abstract: This paper has introduced a diagnostic parameter choosing method for a multiple-input and multiple-output system. This method uses the entropy of the visible diagnostic parameter set as the criterion to classify the heuristic diagnostic parameter set,and on basis of the subset which is decided by the system's current state,forward reasoning is carried out to get a fault subset, regarding which being the object,backward reasoning is used to decide the final fault set. The element's correspendent measurable diagnostic parameters in the final fault set are the desired system's diagnostic parameters. This method can be a part of a diagnostic expert system.

     

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