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为了能够准确地对采煤机变频器进行故障诊断,深入研究了模糊神经网络技术在采煤机变频器故障诊断中的应用。建立了模糊神经网络理论模型,并且对传统的算法进行了改进。设定了模糊神经网络的输入和输出向量,设计出了合理的采煤机变频器模糊神经网络的结构。利用MATLAB数学计算工具对模糊神经网络进行训练,并且进行实验验证,结果表明模糊神经网络能够有效地对采煤机变频器进行故障诊断。
In order to accurately diagnose the fault of shearer frequency converter, the application of fuzzy neural network technology in fault diagnosis of shearer frequency converter is deeply studied. The theoretical model of fuzzy neural network is established, and the traditional algorithm is improved. Set the input and output vectors of fuzzy neural network, and design a reasonable fuzzy neural network structure of the frequency converter. The mathematic calculation tool of MATLAB is used to train the fuzzy neural network and the experiment is carried out. The results show that the fuzzy neural network can effectively diagnose the fault of shearer frequency converter.