节点文献
基于角域平均和连续小波变换的齿轮故障诊断研究
GEAR FAULT DIAGNOSIS BASED ON ANGLE DOMAIN AVERAGE AND CONTINUOUS WAVELET TRANSFORM
【摘要】 针对齿轮箱升降速过程中振动信号非平稳的特点,将阶次跟踪、角域平均和连续小波变换相结合,提出了基于角域平均和连续小波变换的齿轮箱故障诊断方法。首先对齿轮箱升降速瞬态信号进行时域同步采样,再对时域信号进行等角度重采样,转化为角域平稳信号,然后对角域信号进行角域平均,以消除干扰噪声的影响,最后对角域平均信号进行连续小波变换,根据小波幅值图和相位图,就可提取齿轮的故障特征。通过对齿轮齿根裂纹故障实验信号的分析,表明该方法能有效地诊断齿轮的故障状态。
【Abstract】 The order tracking technique, angle domain average technique and continuous wavelet transform (CWT) are introduced and applied specifically to gearbox fault diagnosis during run-up. The angle average technique provides a capability for monitoring gears by presenting the vibration information as a function of the rotating angle of the gear, and enabling a comparison between the vibration produced by those teeth which are presumed healthy and those which are damaged. Then the wavelet amplitude and phase maps of the continuous wavelet transform are used to assess gear damage. The experimental results show that the wavelet amplitude and phase maps both exhibit a characteristic signature in the presence of a cracked tooth.
【Key words】 faults diagnosis; order tracking; angle domain average; continuous wavelet transform; gear;
- 【文献出处】 振动与冲击 ,Journal of Vibration and Shock , 编辑部邮箱 ,2007年11期
- 【分类号】TH132.41
- 【被引频次】26
- 【下载频次】409