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根据矿井提升机主轴装置振动信号进行故障诊断,通过傅里叶变换获得振动信号的频域信号并提取特征参数,将特征参数矩阵输入径向基函数神经网络实现实时振动信号的故障诊断与分类。基于该故障诊断识别方法,联合Visual Basic Net(VB.Net)和MATLAB进行混合编程,开发了矿井提升机实时故障诊断系统。现场试验表明,该故障诊断方法能有效对矿井提升机进行故障诊断,所设计故障诊断系统能在采集矿井提升机振动信号的同时对其故障做出准确诊断分类,满足使用要求。
According to vibration signal of mine hoist spindle device, fault diagnosis is carried out, the frequency domain signal of vibration signal is obtained by Fourier transform and the characteristic parameters are extracted, and the characteristic parameter matrix is input to radial basis function neural network to realize the real-time vibration signal fault diagnosis and classification. Based on the fault diagnosis and identification method, combined with Visual Basic Net (VB.Net) and MATLAB for programming, a mine hoist real-time fault diagnosis system was developed. Field tests show that the fault diagnosis method can effectively diagnose the mine hoist. The designed fault diagnosis system can accurately diagnose and classify the fault of mine hoist while collecting the vibration signal of mine hoist to meet the requirements of the application.