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Fault diagnosis of motor based on mutative scale back propagation net evolving fuzzy Petri nets

机译:基于变比例反向传播网络进化模糊Petri网的电动机故障诊断。

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Aiming at the problem of slow convergence and local optimum in motor fault diagnosis, a new method of motor fault diagnosis based on fuzzy Petri net was proposed, in order to improve the accuracy of fuzzy Petri network diagnosis system, the mutative scale back propagation(BP) algorithm was used to optimize the network parameters, then the classification of several kinds of motor faults were completed by the optimized fuzzy Petri nets. The case analysis shows that the proposed method can effectively distinguish the fault types and has some practical value.
机译:针对电机故障诊断中收敛速度慢和局部最优的问题,提出了一种基于模糊Petri网的电机故障诊断新方法,以提高模糊Petri网诊断系统的变尺度反向传播(BP)。 )算法用于优化网络参数,然后通过优化的模糊Petri网完成几种电机故障的分类。实例分析表明,该方法能够有效地区分故障类型,具有一定的实用价值。

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