将神经网络技术应用于涡流检测信号的自动识别与分类是目前无损检测界关注的问题。
Close attention is paid on the application of neural network technology to automatic recognition and grading of eddy current signals in the field of NDT nowadays.
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。
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.
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