电子测量与仪器学报

钟辉,郭瑜,高国泽.参数自适应 SMHD 滚动轴承 IAS 信号特征提取方法[J].电子测量与仪器学报,2023,37(12):10-17

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

DOI：

英文关键词:rolling bearing instantaneous angular speed sparse maximum harmonics-to-noise-ratio deconvolution parameter adaptation

基金项目: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

作者	单位
钟辉	1.昆明理工大学机电工程学院
郭瑜	1.昆明理工大学机电工程学院
高国泽	1.昆明理工大学机电工程学院

Author	Institution
Zhong Hui	1.Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology
Guo Yu	1.Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology
Gao Guoze	1.Faculty of Mechanical and Electrical Engineering, Kunming University of Science and Technology

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中文摘要:

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。

英文摘要:

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.

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