|
|
|
|
|
|
| Residual Life Prediction of Wet Clutch Based on Oil Spectrum Data
Fusion |
| LIU Yong1, ZHANG Jiang2, XIONG Cen-bo3*, DONG Yi3*, JI Wen-long4, XU Feng4, SHEN Jian2 |
1. School of Energy and Power Engineering, North University of China, Taiyuan 030051, China
2. School of Mechanical and Electrical Engineering, North University of China, Taiyuan 030051, China
3. School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China
4. Unit 32184 of PLA, Beijing 100072, China
|
|
|
|
|
Abstract Aiming at the problems of oil monitoring data of wet clutch, such as scattered sources, a large amount of data and unstable time axis, the multi-data obtained from the spectral analysis are fused. Using the advantages of real-time prediction and accurate prediction of the Wiener process, a model is established to predict the remaining life of the clutch. Firstly, the indicator elements obtained from the clutch life test are fused by permutation entropy weighted evidence fusion method to construct the health index; Secondly, combined with the Wiener process, the degradation model is established, and the parameters in the model are estimated by the maximum likelihood method; Thirdly, the residual life prediction model of the clutch is obtained by updating the parameters according to the historical degradation data; Finally, by comparing the prediction model with an example, it is found that the prediction accuracy of the Wiener process prediction model based on the health index of multi-element fusion is greatly improved compared with the single indicator element prediction. Its prediction point is closer to the experimental value. Through observation, it is also found that when the wet clutch operates for about 50 to 60 h, the prediction point has an obvious change, while the prediction point has an obvious deviation from 220 to 230 h, and it is close to the test value again at about 240 h. The mutation point corresponds to the three stages of clutch wear: initial wear, normal wear and severe wear. The research results show that the prediction model based on oil spectrum data and the Wiener process has the advantages of strong real-time prediction and high prediction accuracy for the remaining life of the wet clutch. The comparison between the prediction results and the test values shows that the different wear states of wet clutch also have a certain impact on the prediction results, especially the wear state transition point has a greater impact on the prediction results.
|
|
Received: 2022-04-27
Accepted: 2022-09-30
|
|
|
|
Corresponding Authors:
XIONG Cen-bo, DONG Yi
E-mail: 798154487@qq.com; dongyi0219@163.com
|
|
[1] BAO He-yun, XU Tong-jing, TAN Wu-zhong, et al(鲍和云，许同晶，谭武中，等). Journal of Central South University(Science and Technology)[中南大学学报(自然科学版)]，2021, 52(4): 1138.
[2] HU Ya-wei, SUN Wen-lei(胡亚威，孙文磊). Machinery Design & Manufacture(机械设计与制造)，2021，(4): 162.
[3] JIN Xiao-hang, XU Zhuang-wei，SUN Yi, et al（金晓航, 许壮伟, 孙 毅，等）. Acta Energiae Solaris Sinica(太阳能学报), 2021, 42(6): 321.
[4] LI Dong-dong, HUA Wei, ZHENG Xiao-xia, et al(李东东, 华 伟, 郑小霞，等). Energiae Solaris Sinica(太阳能学报), 2021, 42(4): 374.
[5] GU Yu-bo, JIA Yun-xian, ZHANG Ying-bo(谷玉波, 贾云献, 张英波). Bearing(轴承), 2013，(4): 44.
[6] Liu K, Gebraeel N Z, Shi J. IEEE Transactions on Automation Science and Engineering, 2013, 10(3): 652.
[7] YAN Shu-fa, MA Biao, ZHENG Chang-song, et al(闫书法，马 彪，郑长松，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2019, 39(2): 553.
[8] ZHANG Quan-de, CHEN Guo, ZHENG Hong-guang, et al(张全德，陈 果，郑宏光，等). Lubrication Engineering(润滑与密封), 2019, 44(3): 128.
[9] RAO Dong-fei, YU Yun-ni（饶冬飞，俞蕴妮）. Journal of Nanchang University(Natural Science)[南昌大学学报（理科版）], 2018, 42(3): 270.
[10] YAN Shu-fa, MA Biao, ZHENG Chang-song(闫书法，马 彪，郑长松). Automotive Engineering(汽车工程), 2019, 41(4): 426.
[11] Xue J Q, Ma B, Chen M, et al. Entropy, 2021, 23: 1704.
[12] Zhao E H, Ma B, Li H Y, et al. Journal of Tribology-Transactions of the ASME, 2018, 140(1): 011401.
[13] LI Le, SHU Yue-chao, WU Jian-peng, et al(李 乐，舒越超，吴健鹏，等). Transactions of Beijing University of Technology(北京理工大学学报), 2022, 42(12): 1246.
[14] FENG Fu-zhou, RAO Guo-qiang, SI Ai-wei, et al(冯辅周，饶国强，司爱威，等). Journal of Armored Forces(装甲兵工程学院学报), 2012, 26(2): 34.
[15] ZHANG Jiang, CUI Jun-jie, ZHENG Chang-song, et al(张 江，崔俊杰，郑长松，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2022, 42(8): 2631.
|
| [1] |
ZHANG Jiang1, CUI Jun-jie1, ZHENG Chang-song2*, LIU Yong1*, LIU Ya-jun3, SHEN Jian1. Stochastic Process Prediction of Clutch Remaining Life Based on Oil
Spectral Data[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(08): 2631-2636. |
| [2] |
SUN Lei1, JIA Yun-xian1, CAI Li-ying2, LIN Guo-yu1, ZHAO Jin-song1, 3 . Research on Engine Remaining Useful Life Prediction Based on Oil Spectrum Analysis and Particle Filtering[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2013, 33(09): 2478-2482. |
|
|
|
|
