基于小波变换振动能量分布的车窗电机故障检测算法研究

Research on window lifter motor fault diagnosis algorithm according WT and vibration energy distribution

针对车窗电机的质量检测问题,对电机的结构、故障原因、振动信号时域、频域、时频特征、能量特征等方面进行了研究,对常见轴承故障频率进行了归纳计算,对传统的傅里叶变换频域检测、希尔伯特—黄变换时频检测进行了应用分析和归纳总结,并在此基础上创新性地结合了小波变换和能量分布概念,提出了一种基于八阶小波变换能量分布的车窗电机故障检测方法,利用振动加速度传感器和Lab View构建了一套完整的采集检测系统,并通过八阶小波变换分解及能量分布曲线构建,对故障和非故障电机的振动信号进行了对比研究。研究结果表明,该系统和方法能有效地反映不同电机的能量分布特征,能够对故障电机和合格电机进行很好的区分,显著提高车窗电机故障检测的效率和准确性。

Aiming at inspecting the quality of window motor,the motor structure,the cause of the problem,the vibration signal of time domain and frequency domain,time-frequency characteristics and energy characteristics were investigated. Common bearing fault frequency were summarized,traditional Fourier transform of frequency domain detecting,Hilbert-huang transform time-frequency analysis were summed up. Based on the innovative concept combines wavelet transform and energy distribution,a window motor fault detection method was presented to calculate the energy distribution after using eight order wavelet transform. A set of complete collection and detection system was constructed by using the vibration acceleration sensor and the Lab View. Vibration signals of the faulted and qualified motors were studied and contrasted through by 8 order wavelet decomposition and the building of energy distribution graph. The results indicate that the system and method can effectively reflect the features of energy distribution of different motors,distinguish faulted and qualified motors very well,and significantly improve the efficiency and accuracy of window motor fault diagnosis.