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A Method of Inverter Circuit fault diagnosis based on BP Neural Network and D-S Evidence Theory

机译:基于BP神经网络和D-S证据理论的逆变电路故障诊断方法。

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With the study and analysis on intelligent fault diagnosis for inverting circuit, an improved diagnosis method combined BP neuron network and D-S evidence theory was proposed. Each measuring point was extracted by BP neural network to obtain the local diagnosis, which is adopted to design the belief function of D-S evidence theory. Multiple monitoring points’ information is fused to receive the comprehensive global diagnosis result. The experimental results show that this method has the better feasibility and effectiveness on fault diagnosis inverter's key components-inverting circuit.
机译:通过对逆变电路智能故障诊断的研究和分析,提出了一种结合BP神经网络和D-S证据理论的改进诊断方法。通过BP神经网络提取每个测量点以获得局部诊断,并以此来设计D-S证据理论的置信函数。融合了多个监视点的信息以接收全面的全局诊断结果。实验结果表明,该方法对故障诊断逆变器关键部件-逆变电路具有较好的可行性和有效性。

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