| 引用本文: | 孙鑫威,纪爱敏,杜占涛,陈曦晖,林新海.动车组齿轮箱滚动轴承变转速故障诊断方法[J].哈尔滨工业大学学报,2023,55(1):106.DOI:10.11918/202205084 |
| SUN Xinwei,JI Aimin,DU Zhantao,CHEN Xihui,LIN Xinhai.Fault diagnosis method for variable speed of rolling bearing in EMU gearbox[J].Journal of Harbin Institute of Technology,2023,55(1):106.DOI:10.11918/202205084 |
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| 摘要: |
| 动车组齿轮箱滚动轴承在运行过程中处于高温重载的变转速工况,容易产生裂纹、点蚀等故障,且不易被检测出来。为及时诊断出动车组齿轮箱滚动轴承的故障,保证动车组的安全行驶,提出了一种变转速工况下的滚动轴承故障诊断方法。首先,结合短时傅里叶变换（STFT）无干扰项与魏格纳-威尔分布（WVD）高时频分辨率的特点,提出了一种融合时频分析算法,该算法能够提高变转速信号分析时的时频矩阵精度；然后,针对动态路径规划方法无法处理归一化时频矩阵的局限性,对其进行了改进,并提取出融合时频矩阵中的转速曲线；此外,进一步提出了一种插值重采样的阶次分析方法,根据转速对采集到的原始信号进行插值重采样,在角域对信号进行重构,并得到对应的阶次谱,实现滚动轴承的故障诊断；最后,通过试验台对提出的变转速动车组故障滚动轴承诊断方法进行了验证。结果表明:本文所提出的方法在动车组转速变化的情况下,能够有效提取出滚动轴承的变转速曲线,并且准确识别出齿轮箱中滚动轴承发生的故障类型。 |
| 关键词: 故障诊断 滚动轴承 融合时频分析 改进的动态路径规划 插值重采样 阶次分析 |
| DOI：10.11918/202205084 |
| 分类号:TN911.7 |
| 文献标识码:A |
| 基金项目:国家自然科学基金(51905147)；江苏省自然科学基金(BK20201163)； 江苏省科技成果转化专项(BA2019020) |
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| Fault diagnosis method for variable speed of rolling bearing in EMU gearbox |
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SUN Xinwei1,JI Aimin1,DU Zhantao1,CHEN Xihui1,LIN Xinhai2
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(1. College of Mechanical and Electrical Engineering,Hohai University, Changzhou 213022, Jiangsu, China; 2. CRRC Qishuyan Institute Co., Ltd., Changzhou 213011, Jiangsu, China)
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| Abstract: |
| The rolling bearing of gearbox of electric multiple-unit (EMU) is in a variable speed condition with high temperature and heavy load during operation, which is easy to induce faults such as cracks and pitting corrosion that are difficult to be detected. In order to diagnose the faults of rolling bearing in gearbox of EMU in time and ensure the safe operation of EMU, a rolling bearing fault diagnosis method under variable speed condition was proposed. First, a fusion time-frequency analysis algorithm was proposed, combining the characteristics of no interference term of short-time Fourier transform (STFT) and high time-frequency resolution of Wigner-Ville distribution (WVD), which can improve the time-frequency matrix accuracy of variable speed signal analysis. Then, the dynamic path planning method was improved considering the limitation that this method cannot deal with the normalized time-frequency matrix, and the speed curves in the fused time-frequency matrix were extracted. Furthermore, an order analysis method of interpolation resampling was proposed. The interpolation resampling of the original signal was performed according to the speed. The signal was reconstructed in the angular domain, and the corresponding order spectrum was obtained to realize the fault diagnosis of rolling bearing. Finally, the proposed fault rolling bearing diagnosis method was verified on test bench, and results showed that the proposed method could effectively extract the variable speed curves of the rolling bearing when the speed of the EMU changed, and accurately identify the fault types of the rolling bearing in the gearbox. |
| Key words: fault diagnosis rolling bearing fusion time-frequency analysis improved dynamic path planning interpolation resampling order analysis |
