冷轧带钢虚拟仪器板形测控系统及其应用
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摘要
针对大宽厚比冷轧带钢复杂板形测控问题,从板形检测单元划分、工艺误差综合补偿、非对称高次板形模式识别、板形统计评价和板形手段协同调控等角度,详细地分析了影响板形测控精度和调控效率的物理机制,并基于机理-智能协同调控模型和虚拟仪器平台,研制了新型的冷轧带钢智能板形测控系统。首先,细化板形检测单元有助有改善带钢边部板形的检测效果,同时还能提高复杂板形缺陷的识别精度;其次,根据各板形控制手段的响应时间和调控特性,实施分层次的组合调控策略,能够充分利用各板形控制手段的调控潜力,避免不同板形控制手段的性能冲突;此外,对在线板形实施智能统计评价,可以准确评估轧机板形控制特性和轧后带钢板形指标,有助于优化板形测控模型。工程案例表明,新型的虚拟仪器板形测控系统闭环周期缩短在100ms以内,板形控制在61以内。
For the complex shape problems of the cold rolling strip with the large width-thickness ratio, according to the shape detection unit, the comprehensive compensation of the process errors, the asymmetrical high-order shape pattern recognition, the shape statistical evaluation and the shape coordinated regulation methods, the physical mechanism of the shape control precision and efficiency are analyzed in detail. Based on the mechanism-intelligence cooperative regulation model and the virtual instrument platform, a new intelligent shape control system of cold rolling strip is developed. First of all, the thinning shape detection unit can not only significantly make the edge shape detection effect of the cold rolling strip better, but also improve the recognition accuracy of complex shape defects. Secondly, taking the response time and the control characteristic of every shape control mean into account, the hierarchical combined regulation strategy can make full use of the shape regulation potential of all shape control means. On the other hand, it is helpful in avoiding the performance conflict of different shape control means. In addition, the online implementation of intelligent statistical evaluation can accurately assess the characteristics of different mills and the shape index of the cold rolling strip, which can optimize the shape control process to a certain extent. The case shows that the close-loop period of the new shape system, based on the virtual instrument platform which significantly improves the shape control efficiency and the control accuracy, is shortened within 100ms, and the shape control is within 6I.
For the complex shape problems of the cold rolling strip with the large width-thickness ratio, according to the shape detection unit, the comprehensive compensation of the process errors, the asymmetrical high-order shape pattern recognition, the shape statistical evaluation and the shape coordinated regulation methods, the physical mechanism of the shape control precision and efficiency are analyzed in detail. Based on the mechanism-intelligence cooperative regulation model and the virtual instrument platform, a new intelligent shape control system of cold rolling strip is developed. First of all, the thinning shape detection unit can not only significantly make the edge shape detection effect of the cold rolling strip better, but also improve the recognition accuracy of complex shape defects. Secondly, taking the response time and the control characteristic of every shape control mean into account, the hierarchical combined regulation strategy can make full use of the shape regulation potential of all shape control means. On the other hand, it is helpful in avoiding the performance conflict of different shape control means. In addition, the online implementation of intelligent statistical evaluation can accurately assess the characteristics of different mills and the shape index of the cold rolling strip, which can optimize the shape control process to a certain extent. The case shows that the close-loop period of the new shape system, based on the virtual instrument platform which significantly improves the shape control efficiency and the control accuracy, is shortened within 100ms, and the shape control is within 6I.
引文
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[10]LIU Hongmin,SHAN Xiuying,JIA Chunyu.Theory-intelligent dynamic matrix model of flatness control for cold rolled strips[J].Journal of Iron and Steel Research,2013,20(8):01-07.
[11]宋蕾,沈明钢,杨利坡,等.冷轧宽带钢板形控制降维功效继承调控方法[J].钢铁,2016,51(1):70-75.SONG Lei,SHEN Minggang,YANG Lipo,et al.Shape control dimensionality reduction efficiency inherited regulation method of cold rolling wide strip[J].Iron and Steel,2016,51(1):70-75.
[12]SONG Lei,SHEN Minggang,YANG Lipo,et al.Effect of width-to-thickness ratio and thickness profile changing on the critical instable shape during cold strip rolling[J].Journal of Shanghai Jiaotong University,2016,21(4):411-418.
[13]闰沁太,张杰,贾生晖,等.冷轧机板形调节能力分析方法的研究与应用[J].机械工程学报,2011,47(4):77-81.YAN Qintai,ZHANG Jie,JIA Shenghui,et al.Research on analyzing the shape adjusting capacity for cold mill and its application[J].Journal of Mechanical Engineering,2011,47(4):77-81.
[14]郝亮,邸洪双,龚殿尧,等.带钢冷轧闭环反馈控制最优化算法程序开发[J].机械工程学报,2012,48(6):39-43.HE Liang,DI Hongshuang,GONG Diangyao,et al.Development of optimization algorithm for closed-loop feedback control in cold strip rolling[J].Chinese Journal of Mechanical Engineering,2012,48(6):39-43.
[15]YANG Lipo,YU Huaxin,WANG Dongcheng,et al.Intelligent shape regulation cooperative model of cold rolling strip and its application[J].Steel Research International,2017,88(7):1-11.
[16]丁顺风,杨利坡,于丙强.基于模糊评判规则的冷轧带钢智能板形评价模型[J].钢铁,2014,49(9):61-63.DING Shunfeng,YANG Lipo,YU Bingqiang.Intelligent model for evaluating cold rolled strip shape based on fuzzy evaluation rule[J].Iron and Steel,2014,49(9):61-63.
[17]丁顺风,杨利坡,于丙强.基于广义极值分布的带钢板形统计模型研究[J].塑性工程学报,2015,22(3):144-147.DING Shunfeng,YANG Lipo,YU Bingqiang.Research on strip shape statistical model based on generalized extreme value distribution[J].Journal of Plasticity Engineering,2015,22(3):144-147.
[18]杨利坡,张永顺,于华鑫,等.冷轧带材板形调控虚拟系统及其应用[J].塑性工程学报,2017,24(5):85-90.YANG Lipo,ZHANG Yongshun,YU Huaxin,et al.Shape control virtual system of cold rolling strip and its application[J].Journal of Plasticity Engineering,2017,24(5):85-90.
[19]BAI Z H,WANG R,CHEN S Y,et al.Online shape prediction and control technology of cold rolled strip during continuous annealing[J].Ironmaking&Steelmaking,2015,42(10):791-796.
[2]刘宏民,刘军,于丙强,等.带钢冷轧机整辊无线式板形仪和智能板形控制系统[J].机械工程学报,2017,53(12):87-93.LIU Hongmin,LIU Jun,YU Bingqiang,et al.Entire roller wireless shape meter and intelligent shape control system for cold steel strip mills[J].Journal of Mechanical Engineering,2017,53(12):87-93.
[3]YANG Lipo,YU Bingqiang,Ding Dong,et al.Industrial shape detecting system of cold rolling strip[J].Journal of Central South University of Technology,2012,19(4):994-1001.
[4]KOZHEVNIKOVА,KOZHEVNIKOVA I,BOLOBANOVA N.Dynamic model of cold strip rolling[J].Metalurgija,2018,57(1-2):99-102.
[5]ZHANG Qingdong,LIN Xiao,CAO Qiang,et al.Flatness evolution of cold-rolled high-strength steel strips during quenching process[J].Advances in Mechanical Engineering,2017,9(12):1-14.
[6]杨利坡,于丙强,李荣民,等.冷轧带钢边部偏移量对原始板形信号的影响[J].钢铁,2014,49(1):52-56.YANG Lipo,YU Bingqiang,LI Rongmin,et al.Effect of strip edge offset on original shape signal of cold rolling strip[J].Iron and Steel,2014,49(1):52-56.
[7]杨利坡,于丙强,李荣民,等.冷轧带钢板形检测误差及异常信号补偿模型[J].机械工程学报,2014,50(6):30-38.YANG Lipo,YU Bingqiang,LI Rongmin,et al.Compensation model of abnormal signal and shape error of cold rolling strip[J].Journal of Mechanical Engineering,2014,50(6):30-38.
[8]杨利坡,于华鑫,袁文越,等.冷轧带材边部板形缺陷精细测控方法[J].塑性工程学报,2017,24(4):28-35.YANG Lipo,YU Huaxin,YUAN Wenyue,et al.Fine control method of edge shape defects for cold rolling strip[J].Journal of Plasticity Engineering,2017,24(4):28-35.
[9]单修迎,刘宏民,贾春玉.含有三次板形的新型板形模式识别方法[J].钢铁,2010,45(8):56-60.SHAN Xiuying,LIU Hongmin,JIA Chunyu.A recognition method of new shape pattern containing the cubic shape[J].Iron and Steel,2010,45(8):56-60.
[10]LIU Hongmin,SHAN Xiuying,JIA Chunyu.Theory-intelligent dynamic matrix model of flatness control for cold rolled strips[J].Journal of Iron and Steel Research,2013,20(8):01-07.
[11]宋蕾,沈明钢,杨利坡,等.冷轧宽带钢板形控制降维功效继承调控方法[J].钢铁,2016,51(1):70-75.SONG Lei,SHEN Minggang,YANG Lipo,et al.Shape control dimensionality reduction efficiency inherited regulation method of cold rolling wide strip[J].Iron and Steel,2016,51(1):70-75.
[12]SONG Lei,SHEN Minggang,YANG Lipo,et al.Effect of width-to-thickness ratio and thickness profile changing on the critical instable shape during cold strip rolling[J].Journal of Shanghai Jiaotong University,2016,21(4):411-418.
[13]闰沁太,张杰,贾生晖,等.冷轧机板形调节能力分析方法的研究与应用[J].机械工程学报,2011,47(4):77-81.YAN Qintai,ZHANG Jie,JIA Shenghui,et al.Research on analyzing the shape adjusting capacity for cold mill and its application[J].Journal of Mechanical Engineering,2011,47(4):77-81.
[14]郝亮,邸洪双,龚殿尧,等.带钢冷轧闭环反馈控制最优化算法程序开发[J].机械工程学报,2012,48(6):39-43.HE Liang,DI Hongshuang,GONG Diangyao,et al.Development of optimization algorithm for closed-loop feedback control in cold strip rolling[J].Chinese Journal of Mechanical Engineering,2012,48(6):39-43.
[15]YANG Lipo,YU Huaxin,WANG Dongcheng,et al.Intelligent shape regulation cooperative model of cold rolling strip and its application[J].Steel Research International,2017,88(7):1-11.
[16]丁顺风,杨利坡,于丙强.基于模糊评判规则的冷轧带钢智能板形评价模型[J].钢铁,2014,49(9):61-63.DING Shunfeng,YANG Lipo,YU Bingqiang.Intelligent model for evaluating cold rolled strip shape based on fuzzy evaluation rule[J].Iron and Steel,2014,49(9):61-63.
[17]丁顺风,杨利坡,于丙强.基于广义极值分布的带钢板形统计模型研究[J].塑性工程学报,2015,22(3):144-147.DING Shunfeng,YANG Lipo,YU Bingqiang.Research on strip shape statistical model based on generalized extreme value distribution[J].Journal of Plasticity Engineering,2015,22(3):144-147.
[18]杨利坡,张永顺,于华鑫,等.冷轧带材板形调控虚拟系统及其应用[J].塑性工程学报,2017,24(5):85-90.YANG Lipo,ZHANG Yongshun,YU Huaxin,et al.Shape control virtual system of cold rolling strip and its application[J].Journal of Plasticity Engineering,2017,24(5):85-90.
[19]BAI Z H,WANG R,CHEN S Y,et al.Online shape prediction and control technology of cold rolled strip during continuous annealing[J].Ironmaking&Steelmaking,2015,42(10):791-796.