节点文献
基于小波神经网络的异步电机故障诊断
Wavelet Neural Network Based Fault Diagnosis of Asynchronous Motor
【Author】 Bo Hu,Wen-hua Tao,Bo Cui,Yi-tong Bai,Xu Yin School of Information & Control Engineering,Liaoning Shihua University,Fushun Liaoning Province 113001,China
【机构】 辽宁石油化工大学信息与控制工程学院;
【摘要】 根据异步电机的复杂故障特点,结合小波变换技术,提出了一种改进的小波神经网络用于异步电机的故障诊断。利用小波变换技术提取异步电机特征信号作为小波神经网络的输入向量,并对小波神经网络算法进行优化,提出了动量项变学习率自适应调整的小波神经网络算法,给出了动量系数和变学习率的调整方法。通过实际测试数据的诊断结果说明该方法的有效性和可行性,具有诊断准确率高、收敛速度快、泛化能力强等优点。
【Abstract】 According to asynchronous motor’s complex fault characteristics,and the combination of wavelet transform technique,an improved wavelet neural network for fault diagnosis of asynchronous motor is proposed in this paper.Taking Wavelet transform technique as wavelet neural network(WNN) the input vector of picking up asynchronous motor’s the characteristic signal,and wavelet neural network algorithm is ptimized,The self-adaptive wavelet neural network algorithm about adjusting momentum vector alter-learning rate is proposed and given the momentum coefficient and alter-learning rate adjustment method.Through the actual testified results show that the method is effective and feasible,and has a better diagnostic accuracy,fast and generalized performances.
【Key words】 Asynchronous motor; Wavelet neural network; Fault diagnosis; Wavelet transformation;
- 【会议录名称】 2009中国控制与决策会议论文集(2)
- 【会议名称】2009中国控制与决策会议
- 【会议时间】2009-06-17
- 【会议地点】中国广西桂林
- 【分类号】TP183;TM343
- 【主办单位】Northeastern University,China、IEEE Industrial Electronics (IE) Chapter,Singapore、Guilin University of Electronic Technology,China