摘要
与AR模型、小波变换等故障诊断方法相比较,工程人员更多的是采用共振解调法对滚动轴承故障进行诊断,但诊断成功与否很大程度上依赖于滤波器中心频率及其带宽的选择。这里提出的诊断滚动轴承故障的自适应共振解调法避免了带通滤波器难以选择的困难。其核心思想是:不采用滤波的方式而是通过先对时间信号进行时频变换,然后从时频能量谱中自动提取时间能量信号的方式来达到将由于冲击引起的共振高频信号和高能量的低频信号分离。此外,给出了一个统一的框架从时频能量谱中自动提取类似于时间边缘的时间能量信号,即Lp范数准则。数值实验结果表明,自适应共振解调法能有效地诊断滚动轴承的外圈故障、内圈故障、滚动体故障,而且比传统的共振解调法的性能更优。
Resonance demodulation method,other than AR model method,wavelet transform method and so on,is adopted by engineers to diagnose faults of rolling bearings of a freight car.But its effectiveness depends to a great extent on how to choose the center frequency and the bandwidth of its filter.The difficulty to choose the band-pass filter can be avoid by the adaptive resonance demodulation method presented here.The key point of the method is to separate high-frequency resonance signals caused by impulse and the low-frequency ones with high energy.The authors firstly do time-frequency transform on the time signal and then automatically extract the time-energy signal from the time-frequency spectrum without filtering.In addition,a uniform frame is proposed to extract the time-energy signal which is similar to time edge from the time-frequency spectrum,which is also called L^p norm criterion.The numerical results show that the adaptive resonance demodulation performs effectively in fault diagnosis of freight car rolling bearings with outer-race faults,inner-race ones and rolling element ones and it performs more effectively than conventional demodulated resonance techniques.
出处
《振动与冲击》
EI
CSCD
北大核心
2007年第1期38-41,共4页
Journal of Vibration and Shock
基金
铁道科学研究院基金项目(2004YF5)资助
关键词
自适应共振解调法
时频分析
L^p范数
细化傅里叶技术
滚动轴承
故障诊断
adaptive resonance demodulation,time-frequency analysis,L^p norm,refined Fourier technique,freight car rolling bearings,fault diagnosis
