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讨论了合成式模糊产生式规则及Petri网故障诊断原理与方法。基于模糊Petri网知识表示模型建立了提升机制动系统故障诊断模型,结合分步式的矩阵推理算法,克服了传统专家系统推理效率低的问题,同时利用故障传播矩阵记录故障的传播过程,体现了故障传播的动态行为,并通过实例验证了算法的正确性。提出了提升机状态监测与模糊Petri网一体化系统模型及其实现方法。充分利用了组态王设备监测与Petri网快速诊断的优势,通过组态王搭建提升机数据监测平台,监测数据经隶属度函数模糊化处理后形成初始标识,输入到模糊Petri网,实现实时监测与动态诊断。
The principles and methods of synthetic fuzzy production rules and Petri nets fault diagnosis are discussed. Based on the knowledge representation model of fuzzy Petri nets, the fault diagnosis model of hoisting machine braking system is established. Combined with the stepwise matrix reasoning algorithm, the problem of low efficiency in traditional reasoning system is overcome. At the same time, fault propagation matrix is used to record the fault propagation process. The dynamic behavior of fault propagation is verified by an example and the correctness of the algorithm is verified. A integrated system model of hoisting machine condition monitoring and fuzzy Petri net and its realization method are put forward. Make full use of the advantages of Kingdee equipment monitoring and Petri nets quick diagnosis, and build the data monitoring platform of hoist through Kingview. The monitoring data is fuzzy processed by membership functions to form the initial identification and input to the fuzzy Petri net for real-time monitoring With dynamic diagnosis.