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。
Currently, RST has been applied in many fields as artificial intelligence, machine learning, data mining, decision support and analysis, process control, pattern recognition, fault detection.
目前，粗糙集理论已被成功地应用在人工智能、机器学习、数据挖掘、决策支持与分析、过程控制、模式识别、故障检测等领域。
Currently, RST has been applied in many fields as artificial intelligence, machine learning, data mining, decision support and analysis, process control, pattern recognition, fault detection.
目前，粗糙集理论已被成功地应用在人工智能、机器学习、数据挖掘、决策支持与分析、过程控制、模式识别、故障检测等领域。
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