Information Entropy Based System's Diagnostic Parameter Choosing Method with Backward and Forward Reasoning
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摘要: 介紹了一種多輸入、多輸出系統的故障診斷參數選擇方法,該方法以可觀參數集的信息熵為標準,進行啟發性診斷參數集的劃分,先以系統狀態決定的啟發性診斷多數子集作為驅動數據,實施正向推理,縮小目標集合;再以故障目標集合為對象,進行反向推理以確定最終故障集合;最后將故障集合的元素所對應的可測診斷參數作為系統的診斷參數進行測量。該方法構成了診斷型專家系統的一子部分。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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