基于故障特征系数模板的变转速滚动轴承故障诊断

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振动与冲击 ›› 2017, Vol. 36 ›› Issue (7) : 123-129.

论文

程卫东,赵德尊,刘东东

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Rolling element bearing fault diagnosis based on fault characteristic coefficienttemplate under time-varying rotating speed

CHENG Weidong,ZHAO Dezun,LIU Dongdong

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文章历史 +

摘要

与恒转速相比，机械中普遍存在的变转速工作模式使滚动轴承的故障诊断更加困难。另外变转速条件下的常规方法—阶比分析存在误差以及计算效率方面的问题。因此，提出了基于故障特征系数模板的滚动轴承故障诊断方法。该方法主要包括以下六部分：(1)根据目标轴承的几何参数计算其故障特征系数以设定模板；(2)利用快速谱峭度滤波算法对滚动轴承振动信号进行滤波；(3)根据Hilbert变换以及短时傅里叶变换计算滤波信号的包络时频图；(4)通过峰值搜索算法从滤波信号的包络时频图中提取瞬时故障特征频率趋势线；(5)根据转速脉冲信号计算滚动轴承的转速曲线；(6)瞬时故障特频率与瞬时转频相比获取瞬时故障特征系数，进而通过故障特征系数模板实现滚动轴承的故障诊断。最后以变转速情况下的故障轴承仿真信号以及实测的外圈故障、内圈故障和健康轴承的振动信号为例验证了该算法的有效性。

Abstract

Compared to constant rotating speed condition,it is more difficult to diagnose bearing faults under time-varying rotating speed.On the other hand,the common method under time-varying rotating speed,i.e.,the order ratio analysis has some problems,such as,larger error and lower computing efficiency.In order to solve these problems,the method of rolling element bearing fault diagnosis based on fault characteristic coefficient template was proposed nere.It consisted of six main steps: ① a template was set up based on the fault characteristic coefficient computed according to geometric parameters of the target bearing; ② the bearing vibration signals were filtered via the fast spectral kurtosis filtering method; ③ the envelope time-frequency figures of the filtered signals were computed based on Hilbert transformation and short time Fourier transformation; ④ the instantaneous fault characteristic frequency trend curve was extracted from the envelope time-frequency figures with the spectral peak search algorithm; ⑤ the speed curve of the bearing was calculated with the rotating speed pulse signals; ⑥ the ratio of the instantaneous fault characteristic frequency to the instantaneous rotating frequency is the instantaneous fault characteristic coefficient for diagnosing the fault type of the bearing.The effectiveness of the proposed method was validated using both simulated and actual measured rolling element bearing faulty vibration signals.

导出引用

程卫东,赵德尊,刘东东. 基于故障特征系数模板的变转速滚动轴承故障诊断[J]. 振动与冲击, 2017, 36(7): 123-129

CHENG Weidong,ZHAO Dezun,LIU Dongdong. Rolling element bearing fault diagnosis based on fault characteristic coefficienttemplate under time-varying rotating speed[J]. Journal of Vibration and Shock, 2017, 36(7): 123-129

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