Crazy Climber算法与重采样技术在消除多普勒效应及列车轴承诊断中的应用  

Application of Crazy Climber algorithm and re-sampling technique in the Doppler effect removal and train bearings diagnosis

作　　者：王超[1] 孔凡让[1] 胡飞[1] 刘方[1] 

机构地区：[1]中国科学技术大学精密机械与精密仪器系,安徽合肥230022

出　　处：《振动工程学报》2014年第5期770-779,共10页Journal of Vibration Engineering

基　　金：国家自然科学基金资助项目(51075379;51475441)

摘　　要：为了提高高速列车道旁轴承状态监测的准确性和可靠性,提出了一种消除信号中多普勒效应的方法。该方法首先应用短时傅里叶变换-Crazy Climber算法求取信号瞬时频率估计,然后结合基于运动学模型的时域重采样原理对信号重采样,重采样得到的信号就是消除了多普勒效应的信号。阐述了短时傅里叶变换-Crazy Climber算法以及时域重采样原理,并与现有方法进行了比较。仿真和实验结果表明,上述方法在去除信号多普勒效应方面具有良好的效果,且易于在道旁轴承监测和故障诊断中实现。Doppler effect widely exists in the signal from the moving acoustic source.With the rapid development and speed-up of modern rail transports,the frequency shift and frequency band expansion resulted from Doppler effect bear heavily on the reliability and accuracy of the wayside Acoustic Defective Bearing Detector（ADBD）system.In order to improve the performance of condition monitoring of the bearings on a passing train with a high speed,the Short Time Fourier Transform-Crazy Climber Algorithm（STFT-CC）is first employed to obtain instantaneous frequency estimation of the distorted signal.Then the necessary parameters for time domain interpolation re-sampling which is totally based on the kinematic analysis are acquired and then the re-sampling sequence could be established in the time domain.The effectiveness of this method is verified by means of simulation studies and applications to the fault diagnosis of train roller bearing defects.The results of the simulation and the experiment indicate that the proposed method has an excellent performance in removing Doppler effect,and could be easily implemented to the condition monitoring and fault diagnosis of train bearings with a high moving speed.

关 键 词：故障诊断 轴承 声音信号 多普勒效应 时域重采样 

分 类 号：TH165.3[机械工程—机械制造及自动化] TB526[理学—物理]