基于CF-PSO-SVM的冷连轧非稳态工作辊弯辊模型优化

doi:10.13228/j.boyuan.issn0449-749x.20210148

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Abstract Flatness quality is an important technical quality specifications of cold rolled strip. At the same time,work roll bending is one of the most effective control methods to improve the flatness quality of cold rolled strip. The strip flatness control precision of tandem cold mill can reach a high level in the process of high speed and stable rolling,but the effect of shape control is not ideal in the process of unsteady rolling,this has also become a negative factor restricting the quality of cold rolled strip. In order to improve the control precision of flatness in the unsteady process of acceleration and deceleration,the principle of bending force setting in tandem cold rolling was studied,combined with the intelligent algorithms and the actual rolling data samples including the strip thickness at the entry and outlet,the tension between the stands,the rolling speed,the middle roll shifting,the strip width,the roll inclination and the rolling force,a bending force prediction strategy based on the support vector machine theory of which parameters were optimized by the particle swarm optimization algorithm was proposed. The principle of support vector machine (SVM) theory and particle swarm optimization (PSO) algorithm was studied. In order to improve the parameters optimization ability,the concepts of compression factor were introduced in the PSO algorithm. Moreover,the PauTa criterion and five-point three-time smoothing method were used to process the relevant rolling data,and then the performance of the prediction strategies was compared by the evaluation indexes,such as mean square error and mean absolute error. The results show that the proposed algorithm was verified with good predictive performance and excellent generalization ability,at the same time,according to the actual production data sample,the compensation model of bending force gap based on rolling speed and roll elasticity coefficient was regressed,and the validity of the model was verified,the model reduced the load of the flatness control system and improved the flatness control precision in unsteady rolling process,the quality pass rate of the head and tail of the product was increased by 5.1%.

Key words： tandem cold rolling flatness control bending force model particle swarm optimization support vector machine

Received: 18 March 2021

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	Articles by authors
	SONG Jun
	REN Ting-zhi
	WANG Kui-yue
	WANG Jun-sheng

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SONG Jun,REN Ting-zhi,WANG Kui-yue等. Optimization of work roll bending model in unsteady process of tandem cold rolling based on CF-PSO-SVM[J]. Iron and Steel, 2021, 56(11): 78-86.

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http://www.chinamet.cn/Jweb_gt/EN/10.13228/j.boyuan.issn0449-749x.20210148 OR http://www.chinamet.cn/Jweb_gt/EN/Y2021/V56/I11/78

[1] 张殿华,孙杰,陈树宗,等. 高精度薄带材冷连轧过程智能优化控制[J]. 钢铁研究学报,2019,31(2):180.(ZHANG Dian-hua,SUN Jie,CHEN Shu-zong,et al. Intelligent optimization control of tandem cold rolling process for high precision thin strip[J]. Journal of Iron and Steel Research,2019,31(2):180.)
[2] 任新意,高慧敏,徐海卫,等. 热镀锌薄带钢穿带堆钢的原因及控制[J]. 上海金属,2021,43(5):91.(REN Xin-yi,GAO Hui-min,XU Hai-wei,et al. Cause and control of piling-up of hot dip galvanized thin strip during threading[J]. Shanghai Metals,2021,43(5):91.)
[3] 郑志刚,李欣伟,程其华,等. 1220五机架冷连轧机板形曲线的改进[J]. 上海金属,2008,30(4):55.(ZHEN Zhi-gang,LI Xin-wei,CHENG Qi-hua,et al. Improvementof shape curve of 1220 5-stand cold tandem mill[J]. Shanghai Metals,2008,30(4):55.)
[4] 刘亚星,张佳胜,白振华. 二次冷轧机组带钢下表面润滑工艺补偿技术[J]. 钢铁,2020,55(7):85.(LIU Ya-xing,ZHANG Jia-sheng,BAI Zhen-hua. Compensation technology of lubrication process for bottom of strip in double cold rolling unit[J]. Iron and Steel,2020,55(7):85.)
[5] 田玉新,陆建生,赵欣. 因瓦合金带材的平整工艺[J]. 上海金属,2019,41(6):97.(TIAN Yu-xin,LU Jian-sheng,ZHAO Xin. Temper rolling process of invar alloy strip[J]. Shanghai Metals,2019,41(6):97.)
[6] 胡柯,沈新玉,曲义振,等. UCM六辊UCM可逆冷轧机带钢断面形状精细控制技术[J].钢铁,2018,53(12):69.(HU Ke,SHEN Xin-yu,QU Yi-zhen,et al. Fine control technology of strip profile for 6-high reversible universal crown cold rolling mill[J]. Iron and Steel,2018,53(12):69.)
[7] WANG P,QIAO D,ZHANG D,et al. Optimal multi-variable flatness control for a cold rolling mill based on a box-constraint optimisation algorithm[J]. Ironmaking and Steelmaking,2016,43(6):426.
[8] 杨光辉,张高尚,张杰,等. 2 180 mm超宽六辊CVC冷轧机SMS-EDC边降控制特性[J].钢铁,2018,53(5):52.(YANG Guang-hui,ZHANG Gao-shang,ZHANG Jie,et al. SMS-EDC edge control characteristics of 2 180 mm super-wide 6-high CVC cold rolling mill[J]. Iron and Steel,2018,53(5):52.)
[9] 任新意,王松涛,高慧敏,等. 冷连轧机ESS辊型板形控制性能分析[J].钢铁,2018,53(3):50.(REN Xin-yi,WANG Song-tao,GAO Hui-min,et al. Analysis on shape control performance of cold tandem mill with ESS roll profile[J]. Iron and Steel,2018,53(3):50.)
[10] CAO J,CHAI X,LI Y,et al. Integrated design of roll contours for strip edge drop and crown control in tandem cold rolling mills[J]. Journal of Materials Processing Technology,2018,252:432.
[11] FENG X,WANG X,SUN J,et al. Analysis of tapered work roll shifting technique in 5-stand UCMW tandem cold rolling process[J]. Australian Journal of Mechanical Engineering,2019,13(2):1.
[12] 王少飞,唐伟,窦爱民,等. 提高CVC冷连轧机板形控制能力的新工艺技术[J]. 冶金自动化,2018,42(3):42.(WANG Shao-fei,TANG Wei,DOU Ai-min,et al. New process technology for improving shape control ability of CVC tandem cold rolling mill[J]. Metallurgical Industry Automation,2018,42(3):42.)
[13] 沈新玉,胡柯,李宏洲,等. UCM冷连轧机边降控制工作辊辊形优化[J].中国冶金,2019,29(11):55.(SHEN Xin-yu,HU Ke,LI Hong-zhou,et al. Work roll contour optimization for edge drop control based on UCM cold rolling mills[J]. China Metallurgy,2019,29(11):55.)
[14] 闻成才,王立兵,刘强,等. 1 580 mm精轧机组大凹辊控制硅钢板形的研究及实践[J].中国冶金,2019,29(1):56.(WEN Cheng-cai,WANG Li-bing,LIU Qiang,et al. Research and practice on controlling of shape of silicon steel plate by large concave roll in hot rolling 1 580 mm finishing mill[J]. China Metallurgy,2019,29(1):56.)
[15] 张卫,李天伦,侯庆龙,等. 基于增量分析和PSO-LSSVM的热轧辊缝调平预测模型[J]. 中国冶金,2021,31(3):122. (ZHANG Wei,LI Tian-lun,HOU Qing-long,et al. Prediction model of hot rolling gap leveling based on incremental analysis and PSO-LSSVM[J]. China Metallurgy,2021,31(3):122.)
[16] 姬亚锋,宋乐宝,原浩,等. 基于KPLS与SVM的热连轧板凸度预测[J]. 中国冶金,2021,31(1):20. (JI Ya-feng,SONG Le-bao,YUAN Hao,et al. Strip crown prediction of hot-rolled strip based on KPLS integrate SVM[J]. China Metallurgy,2021,31(1):20.)
[17] Polyblank J A,Allwood J M,Duncan S R. Closed-loop control of product properties in metal forming:A review and prospectus[J]. Journal of Materials Processing Technology,2014,214(11):2333.
[18] 钱承,张佳胜,白振华,等. 二次冷轧轧辊表面油膜厚度模型及其影响因素[J].钢铁,2020,55(6):68.(QIAN Cheng,ZHANG Jia-sheng,BAI Zhen-hua,et al. Oil film thickness model of roll surface and its influencing factors during double cold rolling[J]. Iron and Steel,2020,55(6):68.)
[19] Rout M,Pal S K,Singh S B. Finite element simulation of a cross rolling process[J]. Journal of Manufacturing Processes,2016,24:283.
[20] 张汉文,仲兆准,黄虎,等. 改进混合粒子群算法优化热轧负荷分配[J]. 轧钢,2021,38(2):55.(ZHANG Han-wen,ZHONG Zhao-zhun,HUANG Hu,et al. Optimization of hot rolling load distribution by improved hybrid particle swarm optimization algorithm[J]. Steel Rolling,2021,38(2):55.)
[21] 张岩,高健,吴鲲魁,等. 单锥度辊冷轧机边部减薄控制应用研究[J]. 冶金自动化,2016,40(1):45.(ZHANG Yan,GAO Jian,WU Kun-kui,et al. Application research for edge drop control on cold mill of single taper roll[J]. Metallurgical Industry Automation,2016,40(1):45.)
[22] 张云锦,邵健,姚驰寰. 马钢热轧CSP锥辊使用技术[J]. 中国冶金,2017,27(9):41.(ZHANG Yun-jin,SHAO Jian,YAO Chi-huan. Application of asymmetric taper roller in Masteel CSP hot rolling[J]. China Metallurgy,2017,27(9):41.)