首页> 外文期刊>International Journal on Smart Sensing and Intelligent Systems >ADAPTIVE DYNAMIC CLONE SELECTION NEURAL NETWORK ALGORITHM FOR MOTOR FAULT DIAGNOSIS
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ADAPTIVE DYNAMIC CLONE SELECTION NEURAL NETWORK ALGORITHM FOR MOTOR FAULT DIAGNOSIS

机译:电机故障诊断的自适应动态克隆选择神经网络算法

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A fault diagnosis method based on adaptive dynamic clone selection neural network(ADCSNN) is proposed in this paper. In this method the weights of neural network is encoded as theantibody, and the network error is considered as the antigen. The algorithm is then applied to faultdetection of motor equipment. The experiments results show that the fault diagnosis method based onADCS neural network has the capability in escaping local minimum and improving the algorithm speed,this gives better performance.
机译:提出了一种基于自适应动态克隆选择神经网络(ADCSNN)的故障诊断方法。该方法将神经网络的权重编码为抗体,将网络错误视为抗原。然后将该算法应用于电机设备的故障检测。实验结果表明,基于ADCS神经网络的故障诊断方法具有逃避局部最小值和提高算法速度的能力,具有较好的性能。

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