摘要
为克服Petri网在推理分析复杂、不确定的故障信息中的不足,引入置信度最大及深度搜索优先的诊断方法,将Petri网和模糊推理知识相结合,提出模糊Petri网故障诊断方法及其概念与规则表示,采用反向推理算法根据已发生的故障来定位故障源,给出推理算法的具体步骤。通过逻辑推理和离心式压缩机故障的实例分析,验证了该算法的有效性和可行性,提高了故障诊断的准确性和高效性。
To overcome the shortcomings of simulating and reasoning complex fuzzy fault information in Petri nets,the confidence level and depth search biggest priority diagnostic methods were introduced,and Petri nets and fuzzy reasoning were combined to put forward the fault diagnosis method,concepts and rules of fuzzy Petri nets.Backward reasoning algorithm based on the fault was used to locate the fault source and the concrete steps of the reasoning algorithm were given.By logical reasoning and analyzing centrifugal compressor fault case,the feasibility and efficiency of the reasoning algorithm are verified,and the accuracy and efficiency of fault diagnosis are improved.
出处
《计算机工程与设计》
北大核心
2018年第1期271-275,共5页
Computer Engineering and Design
