A fault pattern recognition method of power electronic circuits based on two wavelet neural networks is presented.
介绍了一种基于二等分取样，并将预处理数据放大的故障判别神经网络。
A novel method of pattern recognition and fault diagnosis in electrical machine based on the wavelet-neural network is proposed according to the frequency spectrum characteristics of vibration signal.
针对电机振动信号的频谱特点，提出基于小波神经网络技术的电机故障模式识别与诊断的新方法。
The method realizes classification of fault by near-neighborhood criteria of pattern recognition and cellular ant algorithm.
该方法利用模式识别中的近邻准则，使用元胞蚂蚁算法实现故障的分类，达到故障诊断的目的。
This paper studies the fault classification and diagnosis method of the double-bridge 12-pulse waveform controlled rectifier circuit based on pattern recognition.
研究了一种双桥并联可控整流电路的故障分类及诊断方法。
This paper studies the fault classification and diagnosis method of the double-bridge 12-pulse waveform controlled rectifier circuit based on pattern recognition.
研究了一种双桥并联可控整流电路的故障分类及诊断方法。
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