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针对飞机电源故障诊断专家系统中存在的知识表示复杂、不确定性等问题,采用一种基于模糊故障Petri网模型来进行知识表示,同时提出一种正向推理和反向推理相结合的推理算法,该推理算法先用正向推理从故障原因出发,正向查找故障原因导致的故障现象,然后再针对故障现象进行反向推理查找产生此故障的原因,验证故障诊断的真实度。以飞机电源系统中典型故障现象为例,建立故障诊断模型,采用正反结合推理算法加以应用验证,验证结果表明该算法对飞机电源系统故障诊断准确,可操作性强。
Aiming at the complex and uncertain problems of knowledge representation in aircraft power fault diagnosis expert system, a knowledge-based representation model based on fuzzy fault Petri nets is proposed. At the same time, an inference algorithm based on forward reasoning and reverse reasoning is proposed , The reasoning algorithm first uses the forward reasoning to proceed from the cause of the fault and forwardly looks for the fault phenomenon caused by the fault cause, and then performs the reverse reasoning for the fault reason to find out the cause of the fault and verify the fault diagnosis truth degree. Taking a typical fault in the aircraft power system as an example, a fault diagnosis model is established and validated by the forward and reverse combination reasoning algorithm. The verification results show that the algorithm is accurate and operational for aircraft power system fault diagnosis.