Copula-based model for hot-rolling back-up roll health prediction

LI Tian-lun; HE An-rui; SHAO Jian; FU Wen-peng; QIANG Yi; XIE Xiang-qun

doi:10.13374/j.issn2095-9389.2019.08.26.001

Volume 42 Issue 6

Jun. 2020

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Article Navigation > Chinese Journal of Engineering > 2020 > 42(6): 787-795

LI Tian-lun, HE An-rui, SHAO Jian, FU Wen-peng, QIANG Yi, XIE Xiang-qun. Copula-based model for hot-rolling back-up roll health prediction[J]. Chinese Journal of Engineering, 2020, 42(6): 787-795. doi: 10.13374/j.issn2095-9389.2019.08.26.001

Citation:

LI Tian-lun, HE An-rui, SHAO Jian, FU Wen-peng, QIANG Yi, XIE Xiang-qun. Copula-based model for hot-rolling back-up roll health prediction[J]. Chinese Journal of Engineering, 2020, 42(6): 787-795. doi: 10.13374/j.issn2095-9389.2019.08.26.001

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Copula-based model for hot-rolling back-up roll health prediction

doi: 10.13374/j.issn2095-9389.2019.08.26.001

1.
Institute of Engineering Technology, University of Science and Technology Beijing, Beijing 100083, China
2.
Hot Rolling Plant, Meishan Iron & Steel Co. Ltd., Nanjing 210039, China
3.
China Academy of Machinery Science and Technology, Beijing 100044, China

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Corresponding author: E-mail: jianshao@ustb.edu.cn
Received Date: 2019-08-26
Publish Date: 2020-06-01

Abstract

Abstract

The health condition of hot-rolling back-up rolls plays a key role in controlling the strip profile quality and rolling stability. The characteristics of nonlinearity, strong coupling, and the use of limited samples complicate the prediction of the back-up roll health state. The current back-up roll replacement strategy of each steel mill is generally determined according to a certain rolling time or rolling kilometer, and such a maintenance mode is based on experience. In actual experience, due to different strip specifications in each rolling cycle, the degrees of wear on the back-up rolls are different. Regular maintenance methods may easily lead to excessive wear of the back-up rolls and reduce the quality of the strip shape at the end of the unit, or premature roll replacement wastes the back-up roll performance. This paper proposed a construction method for the back-up roll virtual health index and a Copula function–based model for predicting the health condition of complex working conditions. The health condition of a pair of back-up rolls was characterized by combining roll bending and shifting data, and the back-up roll condition was divided by the K-means clustering method. The Copula prediction model was constructed using the process data under each working condition, and finally, according to the actual rolling schedule, the arrangement order combines the prediction results of the working conditions. The production performance data of a 1780-mm hot rolling line were used to verify the results. The results show that the proposed Copula-based prediction model can accurately and effectively predict the health condition of the back-up roll according to the rolling schedule; thus, it can serve as the basis of a more scientific strategy to guide the replacement and maintenance of the back-up roll.
- back-up roll,
- health prognostics,
- Copula function,
- data-driven,
- profile and flatness

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References(25)

References

[1]	沈一鳴. 寶鋼支撐輥的使用技術. 軋鋼, 2004, 21(1):55 doi: 10.3969/j.issn.1003-9996.2004.01.018 Shen Y M. Introduction of application technology of backup roll in Baosteel. Steel Roll, 2004, 21(1): 55 doi: 10.3969/j.issn.1003-9996.2004.01.018
[2]	何安瑞, 張清東, 曹建國, 等. 寬帶鋼熱軋支持輥輥形變化對板形的影響. 北京科技大學學報, 1999, 21(6):565 doi: 10.3321/j.issn:1001-053X.1999.06.015 He A R, Zhang Q D, Cao J G, et al. Effect of back-up roll profile in hot wide strip mill on the strip profile and flatness. J Univ Sci Technol Beijing, 1999, 21(6): 565 doi: 10.3321/j.issn:1001-053X.1999.06.015
[3]	李子文, 高少華, 韓立偉, 等. 承鋼1780節約支撐輥換輥時間//第十屆中國鋼鐵年會暨第六屆寶鋼學術年會論文集. 上海, 2015: 623 Li Z W, Gao S H, Han L W, et al. Chenggang Company 1780 save backup roll roll change time // Proceedings of the 10th CSM Steel Congress & the 6th Baosteel Biennial Academic Conference. Shanghai, 2015: 623
[4]	史志勇, 荊濤, 董寶權, 等. 結合熱軋機組特點合理使用支撐輥//第八屆中國鋼鐵年會論文集. 北京, 2011: 2882 Shi Z Y, Jing T, Dong B Q, et al. Application optimization of BUR according to the mill features // 2011 CSM Annual Meeting Proceedings. Beijing, 2011: 2882
[5]	Alford L D. The problem with aviation COTS. IEEE Aerosp Electron Syst Mag, 2001, 16(2): 33 doi: 10.1109/62.904242
[6]	Gartner D L, Dibbert S E. Application of integrated diagnostic process to non-avionics systems // 2001 IEEE Autotestcon Proceedings. IEEE Systems Readiness Technology Conference. Valley Forge, 2001: 229
[7]	彭宇, 劉大同, 彭喜元. 故障預測與健康管理技術綜述. 電子測量與儀器學報, 2010, 24(1):1 doi: 10.3724/SP.J.1187.2010.00001 Peng Y, Liu D T, Peng X Y. A review: prognostics and health management. J Electron Meas Instrum, 2010, 24(1): 1 doi: 10.3724/SP.J.1187.2010.00001
[8]	馬颯颯, 許愛華, 張群興, 等. 無人機安全監控與健康管理系統研究. 航空維修與工程, 2009(4):63 doi: 10.3969/j.issn.1672-0989.2009.04.027 Ma S S, Xu A H, Zhang Q X, et al. The security monitoring and health management system for UAV. Aviat Mainten Eng, 2009(4): 63 doi: 10.3969/j.issn.1672-0989.2009.04.027
[9]	楊立峰, 王亮, 馮佳晨. 基于PHM技術的導彈維修保障. 海軍航空工程學院學報, 2010, 25(4):447 doi: 10.3969/j.issn.1673-1522.2010.04.020 Yang L F, Wang L, Feng J C. Maintenance support of missile based on PHM technology. J Naval Aeron Astron Univ, 2010, 25(4): 447 doi: 10.3969/j.issn.1673-1522.2010.04.020
[10]	張東, 馮志鵬. 基于變分模式分解和微積分增強能量算子的滾動軸承故障診斷. 工程科學學報, 2016, 38(9):1327 Zhang D, Feng Z P. Fault diagnosis of rolling bearings based on variational mode decomposition and calculus enhanced energy operator. Chin J Eng, 2016, 38(9): 1327
[11]	劉永兵, 周亞凱, 馮志鵬. 形態分量分析在滾動軸承故障診斷中的應用. 工程科學學報, 2017, 39(6):909 Liu Y B, Zhou Y K, Feng Z P. Application of morphological component analysis for rolling element bearing fault diagnosis. Chin J Eng, 2017, 39(6): 909
[12]	張景玲, 楊建華, 唐超權, 等. 基于周期勢系統隨機共振的軸承故障診斷. 工程科學學報, 2018, 40(8):989 Zhang J L, Yang J H, Tang C Q, et al. Bearing fault diagnosis by stochastic resonance method in periodical potential system. Chin J Eng, 2018, 40(8): 989
[13]	趙川, 馮志鵬. 基于多域流形的行星齒輪箱局部故障識別. 工程科學學報, 2017, 39(5):769 Zhao C, Feng Z P. Localized fault identification of planetary gearboxes based on multiple-domain manifold. Chin J Eng, 2017, 39(5): 769
[14]	張東, 馮志鵬. 迭代廣義短時Fourier變換在行星齒輪箱故障診斷中的應用. 工程科學學報, 2017, 39(4):604 Zhang D, Feng Z P. Application of iterative generalized short-time Fourier transform to fault diagnosis of planetary gearboxes. Chin J Eng, 2017, 39(4): 604
[15]	Gugulothu N, Tv V, Malhotra P, et al. Predicting remaining useful life using time series embeddings based on recurrent neural networks // ACM SIGKDD Workshop on Machine Learning for Prognostics and Health Management. Halifax, 2017
[16]	Guo L, Li N P, Jia F, et al. A recurrent neural network based health indicator for remaining useful life prediction of bearings. Neurocomputing, 2017, 240: 98 doi: 10.1016/j.neucom.2017.02.045
[17]	Huang H Z, Wang H K, Li Y F, et al. Support vector machine based estimation of remaining useful life: current research status and future trends. J Mech Sci Technol, 2015, 29(1): 151 doi: 10.1007/s12206-014-1222-z
[18]	Liu J, Zio E. SVM hyperparameters tuning for recursive multi-step-ahead prediction. Neural Comput Appl, 2017, 38: 3749
[19]	高明哲, 許愛強, 許晴. 基于aRVM的電子設備狀態在線預測方法. 兵器裝備工程學報, 2017, 38(11):108 doi: 10.11809/scbgxb2017.11.024 Gao M Z, Xu A Q, Xu Q. Online condition prediction of electronic equipment based on relevance vector machine with adaptive Kernel learning. J Ordnance Equip Eng, 2017, 38(11): 108 doi: 10.11809/scbgxb2017.11.024
[20]	Zermani S, Dezan C, Chenini H, et al. FPGA implementation of Bayesian network inference for an embedded diagnosis // 2015 IEEE Conference on Prognostics and Health Management. Austin, 2015: 1
[21]	Zermani S, Dezan C, Euler R, et al. Bayesian network-based framework for the design of reconfigurable health management monitors // 2015 NASA/ESA Conference on Adaptive Hardware and Systems. Montreal, 2015: 1
[22]	Wang T Y, Yu J B, Siegel D, et al. A similarity-based prognostics approach for remaining useful life estimation of engineered systems // International Conference on Prognostics and Health Management. Denver, 2008: 1
[23]	朱揚普. 無損檢測技術在軋輥檢測中的推廣及應用. 機電工程技術, 2016, 45(5):121 doi: 10.3969/j.issn.1009-9492.2016.05.034 Zhu Y P. Generalization and application of NDT technology in roller testing. Mech Electr Eng Technol, 2016, 45(5): 121 doi: 10.3969/j.issn.1009-9492.2016.05.034
[24]	何安瑞, 邵鍵, 孫文權. 板形控制理論與實踐. 北京: 冶金工業出版社, 2016 He A R, Shao J, Sun W Q. Theory and Practice of Shape Control. Beijing: Metallurgical Industry Press, 2016
[25]	Nelsen R B. An Introduction to Copulas. Technometrics, 2000, 42(3): 317