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

作　　者：李辉[1] 郑海起[2] 杨绍普[3] 

机构地区：[1]北京交通大学机械与电子控制工程学院,北京100044 [2]军械工程学院一系,石家庄050003 [3]石家庄铁道学院机械工程系,石家庄050043

出　　处：《振动与冲击》2007年第11期16-19,共4页Journal of Vibration and Shock

基　　金：国家自然科学基金资助项目(50375157)

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。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.

关 键 词：故障诊断 阶次跟踪 角域平均 连续小波变换 齿轮 

分 类 号：TH115[机械工程—机械设计及理论]