关于码垛机器人机电系统故障建模诊断仿真

Simulation of Fault Modeling and Diagnosis of Electromechanical System of Palletizing

由于码垛机器人的机电系统故障具有不确定性、模糊性,传统的分析方法对事件的概率重要度计算繁琐且故障诊断具有盲目性。为解决上述问题,提出了基于模糊Petri网(FPN)的机电系统故障建模及推理方法。该方法通过分析故障原因以及各故障之间的内在关系,建立了基于FPN的机电系统故障诊断模型;利用FPN的正向矩阵推理对机电系统的子系统进行可靠性分析,求出了目标库所的概率重要度,对于已经发生的故障采取反向推理的方法对机电系统进行故障诊断,寻找故障源。通过仿真验证了该机电系统故障建模及推理方法能够高效的计算概率重要度,并消除了机电系统故障诊断的盲目性。

Due to the uncertainty and ambiguity of the electromechanical system fault of the palletizing robot,traditional analysis method is cumbersome in calculating the probability importance of the event and the blindness of the fault diagnosis.In order to solve the above problems,a fuzzy Petri net (FPN)based fault modeling and reasoning method for electromechanical systems is proposed.By analyzing the cause of the fault and the inherent relationship between the faults,the fault diagnosis model of the electromechanical system based on FPN was established.The forward matrix inference of FPN was used to analyze the reliability of the subsystem of the electromechanical system, and the probability importance of the target library was obtained.For faults that have already occurred,a reverse reasoning method was used to diagnose the electromechanical system and find the source of the faults.The simulation proves that the electromechanical system fault modeling and reasoning method can efficiently calculate the probability importance and eliminate the blindness of the electromechanical system fault diagnosis.'