参数自适应SMHD滚动轴承IAS信号特征提取方法  

Parameter adaptive SMHD rolling bearing IAS signal feature extraction method

作　　者：钟辉 郭瑜[1] 高国泽 Zhong Hui;Guo Yu;Gao Guoze(Faculty of Mechanical and Electrical Engineering,Kunming University of Science and Technology,Kunming 650500,China)

机构地区：[1]昆明理工大学机电工程学院,昆明650500

出　　处：《电子测量与仪器学报》2023年第12期10-17,共8页Journal of Electronic Measurement and Instrumentation

基　　金：国家自然科学基金(5216507);云南省重点领域科技计划项目(202002AC080001)资助。

摘　　要：针对编码器瞬时角速度(IAS)信号中滚动轴承故障特征提取困难的问题,结合稀疏最大谐波噪声比解卷积(SMHD)算法可在没有先验周期情况下提取信号中周期性脉冲故障分量的优势提出一种参数自适应SMHD滚动轴承IAS信号特征提取方法。首先,利用向前差分法估计IAS信号;然后,利用故障特征(FC)作为自适应选取SMHD优化滤波器长度的评判指标,实现SMHD滤波器长度的自适应确定;再将优化选取的滤波器长度代入SMHD算法对IAS信号进行增强。最后,通过包络分析揭示滚动轴承故障特征。通过对仿真和实测数据进行分析,验证了所提方法的有效性。Aiming at the difficulty of rolling bearing fault feature extraction in the encoder instantaneous angular speed(IAS)signal,a parameter-adaptive SMHD rolling bearing IAS signal feature extraction method is proposed by combining the advantages of the sparse maximum harmonics-to-noise-ratio deconvolution(SMHD)algorithm,which can extract the periodic impulse fault component in the signal without a priori period.Firstly,the IAS signal is estimated using the forward difference method.Then,the fault characteristics(FC)are utilized as an adaptive criterion for selecting the optimal length of the SMHD filter,achieving adaptive determination of the filter length.Subsequently,the optimized filter length is applied to enhance the IAS signal using the SMHD algorithm.Finally,the fault characteristics of the rolling bearing are revealed through envelope analysis.The effectiveness of the proposed method is validated through analysis of both simulated and measured data.

关 键 词：滚动轴承 瞬时角速度 稀疏最大谐波噪声比解卷积 参数自适应 

分 类 号：TN762[电子电信—电路与系统] TH165.3[机械工程—机械制造及自动化]