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文章阐述了设备故障诊断步骤优化的必要性和前期研究概况。指出了,采用人工智能与或树启发式搜索的可行性及先进性。以故障条件概率和搜索检测代价组成启发函数。给出了,与门和或门情况下故障条件概率自上而下的传递规则、启发式搜索算法以及剪枝方法。应用了设备诊断可达性的量化表达式。最后举出柴油机润滑系统故障诊断实例予以说明。
The paper elaborates the necessity of optimization of equipment fault diagnosis and the overview of previous research. Pointed out the feasibility and advancedness of using artificial intelligence and / or tree heuristic search. The heuristic function is composed of fault conditional probability and search detection cost. The top-down rules of failure probability, heuristic search algorithm and pruning method are given in the case of AND-OR gate. Quantified expression with diagnostic reachability of the device. Finally, the diesel engine lubrication system fault diagnosis examples to be explained.