【摘要】 为诊断蜗杆减速机的蜗轮齿形变化故障,提出了一种新的振动信号特征检测方法,即将自相关分析方法与传统的齿轮故障分析方法经验模态分解及Hilbert变换相结合的方法。采用经验模态分解,将蜗杆减速机振动信号分离为各个不同频率段的本征模态函数(IMF)分量,运用自相关分析高效选取含有蜗轮故障特征信号的IMF分量,最后应用Hilbert变换提取由自相关算法选取的IMF分量中蜗轮故障特征信息。采用JD45+齿轮测量仪分析了蜗轮齿形变化量,验证了上述方法的可行性。更多还原

【Abstract】 In order to diagnosis the fault of worm reducer caused by worm gear tooth profile changed,a new vibration signal detection method is proposed.The new method was that autocorrelation analysis was referenced to traditional gear fault analysis method which were empirical mode decomposition(EMD) and Hilbert transform.The worm reducer vibration signal were separated to different intrinsic mode functions component in different frequency(IMF).The autocorrelation analysis method is used to select IMF component which containing worm gear fault characteristic signal efficiently.Finally,the fault feature of IMF component is extracted by Hilbert transform.The JD45 + measuring instrument measuring the changed amount of worm gear tooth profile is used to verify the feasibility of this method.更多还原