变转速工况下滚动轴承时频脊线提取易受噪声等干扰信号影响,导致提取的时频脊线偏离真实值,从而影响故障诊断精度.本文提出一种基于滑动窗多时频脊线提取的滚动轴承变转速故障诊断方法.首先,利用二阶同步压缩短时傅里叶变换获取轴承故障信号高分辨率时频表示;然后,基于滑动窗从时频图中迭代提取多条特征脊线,有效排除噪声及相邻分量干扰,准确估计轴承的瞬时旋转频率及瞬时故障特征频率;最后,依据瞬时故障特征频率与瞬时旋转频率的比值判断轴承故障类型.滚动轴承变转速故障仿真及实验分析结果表明,本研究方法具有良好的噪声鲁棒性,其特征脊线提取效果优于经典的多时频曲线提取方法.
The extraction of time-frequency ridge of rolling bearing is susceptible to noise and other interfering signals under variable speed conditions, leading to the extracted ridge to deviate from the true value thereby, and affecting the accuracy of fault diagnosis. A variable speed rolling bearing fault diagnosis method based on sliding window multi-time-frequency ridge extraction is proposed in this work. First, the high-resolution time-frequency representation of bearing fault signal is obtained by using the second-order synchrosqueezing short-time Fourier transform. Next, multiple feature ridges are extracted iteratively from the time-frequency map based on the sliding window, to effectively eliminate the noise and adjacent-component interference, and to accurately estimate the instantaneous rotational frequency and instantaneous fault-characteristic frequency of the bearing. Finally, the bearing fault type is identified by the ratio of instantaneous fault-characteristic frequency to instantaneous rotational frequency. Simulation and experimental analysis results of rolling bearing variable speed fault show that the proposed method has- DOI:10.3969/j.issn.1000-1565.2025.05.011基于滑动窗多时频脊线提取的滚动轴承变转速故障诊断郝紫阳1,张晓宣1,冯贺平2(1.河北大学 质量技术监督学院,河北 保定 071002;2.河北软件职业技术学院 智能工程系,河北 保定 071002)摘 要:变转速工况下滚动轴承时频脊线提取易受噪声等干扰信号影响,导致提取的时频脊线偏离真实值,从而影响故障诊断精度.本文提出一种基于滑动窗多时频脊线提取的滚动轴承变转速故障诊断方法.首先,利用二阶同步压缩短时傅里叶变换获取轴承故障信号高分辨率时频表示;然后,基于滑动窗从时频图中迭代提取多条特征脊线,有效排除噪声及相邻分量干扰,准确估计轴承的瞬时旋转频率及瞬时故障特征频率;最后,依据瞬时故障特征频率与瞬时旋转频率的比值判断轴承故障类型.滚动轴承变转速故障仿真及实验分析结果表明,本研究方法具有良好的噪声鲁棒性,其特征脊线提取效果优于经典的多时频曲线提取方法.关键词:时频脊线提取;变转速;滚动轴承;故障诊断中图分类号:TH133.3 文献标志码:A 文章编号:1000-1565(2025)05-0551-10Variable speed fault diagnosis of rolling bearings based on sliding-window multiple time-frequency ridge extractionHAO Ziyang1, ZHANG Xiaoxuan1, FENG Heping2(1. College of Quality and Technical Supervision, Hebei University,Baoding 071002, China;2. Intelligent Engineering Department, Hebei Software Institute, Baoding 071002, China)Abstract: The extraction of time-frequency ridge of rolling bearing is susceptible to noise and other interfering signals under variable speed conditions, leading to the extracted ridge to deviate from the true value thereby, and affecting the accuracy of fault diagnosis. A variable speed rolling bearing fault diagnosis method based on sliding window multi-time-frequency ridge extraction is proposed in this work. First, the high-resolution time-frequency representation of bearing fault signal is obtained by using the second-order synchrosqueezing short-time Fourier transform. Next, multiple feature ridges are extracted iteratively from the time-frequency map based on the sliding window, to effectively eliminate the noise and adjacent-component interference, and to accurately estimate the instantaneous rotational frequency and instantaneous fault-characteristic frequency of the bearing. Finally, the bearing fault type is identified by the ratio of instantaneous fault-characteristic frequency to instantaneous rotational frequency. Simulation and experimental analysis results of rolling bearing variable speed fault show that the proposed method has- 收稿日期:2025-03-11;修回日期:2025-07-11 基金项目:河北省自然科学基金项目(E2021201032) 第一作者:郝紫阳(1977—),男,河北大学讲师,主要从事机械装备状态监测与故障诊断研究.E-mail:haoziyang@hbu.edu.cn 通信作者:冯贺平(1979—),女,河北软件职业技术学院副教授,主要从事方程智能检测、智能控制研究.Email:fengheping@126.com第5期郝紫阳等:基于滑动窗多时频脊线提取的滚动轴承变转速故障诊断河北大学学报(自然科学版) 第45卷good noise robustness, and its feature ridge extraction effect is better than the classical multiple time-frequency curve extraction method.
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