| 张文灏,沙云东,栾孝驰,赵俊豪,蒋函岐.基于CEEMDAN-MPE-VMD多分量筛选融合的滚动轴承故障提取方法[J].装备环境工程,2024,21(9):50-60. ZHANG Wenhao,SHA Yundong,LUAN Xiaochi,ZHAO Junhao,JIANG Hanqi.Rolling Bearing Fault Extraction Method Based on CEEMDAN-MPE-VMD Multi-component Screening Fusion[J].Equipment Environmental Engineering,2024,21(9):50-60. |
| 基于CEEMDAN-MPE-VMD多分量筛选融合的滚动轴承故障提取方法 |
| Rolling Bearing Fault Extraction Method Based on CEEMDAN-MPE-VMD Multi-component Screening Fusion |
| 投稿时间：2024-08-10 修订日期：2024-09-18 |
| DOI：10.7643/issn.1672-9242.2024.09.007 |
| 中文关键词: 航空发动机 滚动轴承 分量筛选融合 CEEMDAN VMD 故障诊断中图分类号:V216 文献标志码:A 文章编号:1672-9242(2024)09-0050-11 |
| 英文关键词:aero-engine rolling bearing component screening fusion CEEMDAN VMD fault diagnosis |
| 基金项目:中国航发产学研合作项目(HFZL2018CXY017) |
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| Author | Institution |
| ZHANG Wenhao | School of Aero-engine, Shenyang Aerospace University, Shenyang 110136, China |
| SHA Yundong | School of Aero-engine, Shenyang Aerospace University, Shenyang 110136, China |
| LUAN Xiaochi | School of Aero-engine, Shenyang Aerospace University, Shenyang 110136, China |
| ZHAO Junhao | School of Aero-engine, Shenyang Aerospace University, Shenyang 110136, China |
| JIANG Hanqi | School of Aero-engine, Shenyang Aerospace University, Shenyang 110136, China |
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| 中文摘要: |
| 目的 针对航空发动机机械系统滚动轴承故障诊断难的问题，提出一种基于CEEMDAN-MPE-VMD多分量筛选融合的滚动轴承故障提取方法。方法 用自适应噪声集合经验经验模态(简称CEEMDAN)分解强干扰环境复杂传递路径下测得的滚动轴承振动信号，得到若干个节点分量，筛选出相对MPE较大的前5个分量(IMF1~IMF5)。然后以变分模态分解(VMD)分别分解此5个分量，筛选出每个分量MPE较大的前4个分量(imf1-imf4)，再将此5组的4个分量(imf1~imf4)分别重构，得到新的IMF1~IMF5，与之前的IMF10-IMF14重构，并进行包络解调，识别故障特征信息。结果 基于西储大学实验数据和滚动轴承实验台测试数据，综合验证了该振动信号提取方法的有效性，并完成了航空发动机中介轴承模拟试验台所测数据的故障识别。结论 该方法可有效提取滚动轴承在简单及复杂传递路径下的故障特征，可作为提取航空发动机主轴轴承特征和诊断方法之一。 |
| 英文摘要: |
| Aiming at the difficulty of fault diagnosis of rolling bearing in aero-engine mechanical system, the work aims to propose a fault extraction method of rolling bearing based on CEEMDAN-MPE-VMD multi-component screening fusion. The adaptive noise complete empirical mode decomposition (CEEMDAN) was used to decompose the rolling bearing vibration signal measured under the complex transmission path of strong interference environment, and several node components were obtained. The first five components (IMF1-IMF5) with larger relative MPE were selected, and then the five components were decomposed by variational mode decomposition (VMD). The first four components (imf1-imf4) with larger MPE of each component were selected again, and then the four components (imf1-imf4) of these five groups were reconstructed respectively to obtain a new (IMF1-IMF5), which was reconstructed with the previous IMF10-IMF14 for envelope demodulation to identify fault feature information. Based on the experimental data of Xichu University and the test data of the rolling bearing test bench, the effectiveness of the vibration signal extraction method was comprehensively verified, and the fault identification was carried out on the data measured by the aero-engine intermediate bearing simulation test bench. The results show that this method can effectively extract the fault features of rolling bearings under simple and complex transmission paths, and can be used as one of the methods to extract the features and carry out diagnosis of aero-engine spindle bearings. |
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