整辊智能型冷轧带钢板形仪研制及工业应用
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摘要
板形是高级冷轧带钢的重要质量指标,板形控制是冷轧带钢轧机的核心技术、关键技术、前沿技术和高端技术。板形仪是在线检测板形的“眼睛”,是实现板形闭环控制的前提和关键。我国在冷轧板形控制方面一直受制于人,虽然近三十年来,国内在该领域取得了一些突破性技术进步,但是对于板形仪的研究始终处于实验室实验阶段,工业应用几乎空白。尤其对于板形仪核心关键部件——检测辊的研究,国内始终效仿国外已有产品,设计理念没有重大革新。这使得闭环控制技术一直被国外几家大公司封锁和垄断,引进和维护费用极为昂贵,目前国内仅少数大型企业引进。由于难以后续技术升级和工艺优化,一直不能稳定生产高级精品带钢产品,导致一流轧机生产不出一流产品,用户满意度普遍较低。目前,国内亟待解决板形检测和闭环控制这一冷轧领域内的最棘手难题,因此自主创新研制满足工业应用的板形仪,其意义重大而关键。
本文突破国际上流行的技术方案,成功研制满足工业应用的整辊镶块式冷轧带钢智能型板形仪。首先,提出与国际流行分段式板形仪不同的创新理念,将安装传感器的弹性块镶嵌于检测辊径向对称两个矩形通槽内,构成整辊式辊体结构,信号灵敏度高,避免划伤带钢表面。其次,研制高度集成自动喷淋式集流装置,实现集流环的自动清洗、润滑和冷却,显著提高信号稳定性和集流环使用寿命。第三,研制变包角模拟标定装置,增强标定功能,实现板形仪的动态精确标定,提高标定精度和检测精度。第四,研制嵌入式DSP板形信号处理硬件系统,提高板形信号的抗干扰能力、可靠性和实时性。第五,研发具有误差补偿、标准曲线、模式识别、板形控制功能的板形信号处理软件系统,提高板形仪的智能化水平。上述关键技术不仅适用于连轧机,也适用于单机架可逆轧机、平整机、拉矫机等。目前,该板形仪已成功应用于鞍钢1250 mm冷轧机上,整体技术指标达到了国际同行业的领先水平。
该板形仪的研制成功,实现了冷轧带钢板形检测和板形控制这一核心关键技术的自主创新,突破了国外的技术封锁和垄断。有助于整体上提升我国冷轧机的装备水平,满足生产高水平精品带钢产品的技术要求,提高高级冷轧带钢产品的用户满意度,满足我国汽车板、家电板、装饰板、涂镀板等高端冷轧产品的市场需求。
The strip shape is important qualitative index of the high-level cold-strip steel, the shape control is the core technology, the key technology, the frontier technology and the high-end technology of the cold-strip steel rolling mill. The shape meter is the“eye”for online examinating shape strip, and is the premise and the key of realizing the shape closed-loop control.The cold rolling domain's shape control aspect has been controlled by others, although the last three decades, China has made in this area some breakthrough advances in technology, but for the shape meter is always in laboratory research stage, the industrial application is almost blank. The key components of the core shape meter- Measuring Roll research, always following the foreign product , without major innovation in design. This makes the closed-loop control technology blocked by foreign companies and several major monopolies, leading to the introduction and maintenance is extremely expensive, only a small number of large domestic enterprises to introduce. But because of it is difficult in technical upgrades and process optimization follow-up, it is difficult to produce high quality strip steel product steadily, excellent mill no first-class products, customer satisfaction is generally low. At present, it si desiderate to solve the shape measurement and closed loop control in the area of the cold rolling and it is the most difficult problems.So the development of independent innovation to meet the shape meter for industrial applications is significant and critical.
This paper breakthrough the international and popular technology program, successfully developed to meet industrial application of the entire roll inserts cold rolling strip-shaped instrument smart plate. Firstly, proposed an innovative concept different from international instrument popular sectional shape, the installed sensors’s elastic block embedded in two rectangular tank of detection roll radial symmetry, constitute the entire roll body roll-type structure, signal sensitivity, to avoid scratch the surface of strip. Secondly, develop flow automatic spray which is set of highly integrate device ,to achieve slip ring of the self-cleaning, lubrication and cooling, significantly improved signal’s stability and slip ring’s service life. Thirdly, develop the device of variable packet angle calibration simulation, enhanced calibration function, to achieve the shape of dynamic precision calibration, to improve the calibration accuracy and precision. Fourthly, develop the hardware system of embedded DSP shap signal processing, to improve shape signal anti-jamming capability, reliability and real-time. Fifthly, research and develop with error compensation, the standard curve, pattern recognition, shape control function of the shape signal processing software system to enhance the shape meter Engineer. The key technologies applied not only to mill, also applies to single stand reversing mill, leveling mill, tension and leveling. Currently, the instrument has been successfully applied to the cold rolling mill in Anshan Iron and Steel 1250 mm, the overall technical indicators have reached international leading level in the same industry.
The successful development of the shape meter, realized the independent innovation in the key technologies of cold rolled steel shape detection and shape control break,through the blockade and the monopoly of foreign technology. Help raise the overall level of China's cold rolling mill equipment, meet the technical requirement of producing high quality strip steel products, improve high customer satisfaction of cold-rolled strip steel products, and meet the cold rolled products demand of car plate, home appliance plate, decorative plate, coated board and other high-end market.
本文突破国际上流行的技术方案,成功研制满足工业应用的整辊镶块式冷轧带钢智能型板形仪。首先,提出与国际流行分段式板形仪不同的创新理念,将安装传感器的弹性块镶嵌于检测辊径向对称两个矩形通槽内,构成整辊式辊体结构,信号灵敏度高,避免划伤带钢表面。其次,研制高度集成自动喷淋式集流装置,实现集流环的自动清洗、润滑和冷却,显著提高信号稳定性和集流环使用寿命。第三,研制变包角模拟标定装置,增强标定功能,实现板形仪的动态精确标定,提高标定精度和检测精度。第四,研制嵌入式DSP板形信号处理硬件系统,提高板形信号的抗干扰能力、可靠性和实时性。第五,研发具有误差补偿、标准曲线、模式识别、板形控制功能的板形信号处理软件系统,提高板形仪的智能化水平。上述关键技术不仅适用于连轧机,也适用于单机架可逆轧机、平整机、拉矫机等。目前,该板形仪已成功应用于鞍钢1250 mm冷轧机上,整体技术指标达到了国际同行业的领先水平。
该板形仪的研制成功,实现了冷轧带钢板形检测和板形控制这一核心关键技术的自主创新,突破了国外的技术封锁和垄断。有助于整体上提升我国冷轧机的装备水平,满足生产高水平精品带钢产品的技术要求,提高高级冷轧带钢产品的用户满意度,满足我国汽车板、家电板、装饰板、涂镀板等高端冷轧产品的市场需求。
The strip shape is important qualitative index of the high-level cold-strip steel, the shape control is the core technology, the key technology, the frontier technology and the high-end technology of the cold-strip steel rolling mill. The shape meter is the“eye”for online examinating shape strip, and is the premise and the key of realizing the shape closed-loop control.The cold rolling domain's shape control aspect has been controlled by others, although the last three decades, China has made in this area some breakthrough advances in technology, but for the shape meter is always in laboratory research stage, the industrial application is almost blank. The key components of the core shape meter- Measuring Roll research, always following the foreign product , without major innovation in design. This makes the closed-loop control technology blocked by foreign companies and several major monopolies, leading to the introduction and maintenance is extremely expensive, only a small number of large domestic enterprises to introduce. But because of it is difficult in technical upgrades and process optimization follow-up, it is difficult to produce high quality strip steel product steadily, excellent mill no first-class products, customer satisfaction is generally low. At present, it si desiderate to solve the shape measurement and closed loop control in the area of the cold rolling and it is the most difficult problems.So the development of independent innovation to meet the shape meter for industrial applications is significant and critical.
This paper breakthrough the international and popular technology program, successfully developed to meet industrial application of the entire roll inserts cold rolling strip-shaped instrument smart plate. Firstly, proposed an innovative concept different from international instrument popular sectional shape, the installed sensors’s elastic block embedded in two rectangular tank of detection roll radial symmetry, constitute the entire roll body roll-type structure, signal sensitivity, to avoid scratch the surface of strip. Secondly, develop flow automatic spray which is set of highly integrate device ,to achieve slip ring of the self-cleaning, lubrication and cooling, significantly improved signal’s stability and slip ring’s service life. Thirdly, develop the device of variable packet angle calibration simulation, enhanced calibration function, to achieve the shape of dynamic precision calibration, to improve the calibration accuracy and precision. Fourthly, develop the hardware system of embedded DSP shap signal processing, to improve shape signal anti-jamming capability, reliability and real-time. Fifthly, research and develop with error compensation, the standard curve, pattern recognition, shape control function of the shape signal processing software system to enhance the shape meter Engineer. The key technologies applied not only to mill, also applies to single stand reversing mill, leveling mill, tension and leveling. Currently, the instrument has been successfully applied to the cold rolling mill in Anshan Iron and Steel 1250 mm, the overall technical indicators have reached international leading level in the same industry.
The successful development of the shape meter, realized the independent innovation in the key technologies of cold rolled steel shape detection and shape control break,through the blockade and the monopoly of foreign technology. Help raise the overall level of China's cold rolling mill equipment, meet the technical requirement of producing high quality strip steel products, improve high customer satisfaction of cold-rolled strip steel products, and meet the cold rolled products demand of car plate, home appliance plate, decorative plate, coated board and other high-end market.
引文
1连家创,刘宏民.板厚板形控制.北京:兵器工业出版社,1996:41-99
2王国栋.板形控制和板形理论.北京:冶金工业出版社,1986:1-20
3王国栋,刘相华,王军生.冷连轧生产工艺的进展.轧钢, 2003,20(1):37-41
4丁修堃.轧制过程自动化.北京:冶金工业出版社, 2005:206-210
5刘玠.冷轧生产自动化技术.北京:冶金工业出版社, 2006:95-105
6徐乐江.板带冷轧机板形控制与机型选择.北京:冶金工业出版社,2007:217-223
7庞玉华,钟春生,王经涛,等.冷轧带材板形检测计算机模拟研究.重型机械,2000,4:24-27
8王快社,赵远攀,钟春生.基于人工神经网络的一种板形检测方法研究.冶金设备,2002,134(4): 12-14
9庞玉华,钟春生,王经涛.基于子波理论的板形检测信号分析研究.金属成形工艺,2000,18(6): 7-9
10赵小燕,张朝晖,迟健男.基于张力测量的板形检测技术.制造业自动化,2007,29(3):90-92
11毛小春,杨西荣,钟春生.快速付里叶变换在板形检测中的应用.重型机械,2004,3:53-58
12庞玉华,毛晓春,钟春生.新型分段辊式动态板形检测仪.重型机械,1999,1:10-14
13庞玉华,钟春生,王经涛.轧钢板形检测仪研究动向.上海金属,2001,23(2):10-13
14王训宏,王快社,杨西荣,等.新型接触式板形检测辊的研制.冶金设备,2005,154(6):54-57
15钟春生,庞玉华,毛小春.板形检测方法研究趋向浅析.1998,6:1-5
16杨景明,王振臣.板形检测辊输出信号的通道处理方法.自动化仪表,1997,18(5):34-38
17张勇,李长江,何正春.计算机图像处理技术在钢板板形检测中的应用.重庆工业高等专科学校学报,2002,17(1):43-47
18白振华.冷连轧机高速生产过程核心工艺数学模型.北京:机械工业出版社,2009:1-95
19白振华,刘宏民,李秀军,等.平整轧制工艺模型.北京:冶金工业出版社,2010:1-20
20王清洁.板形仪控制技术在森吉米尔轧机上的应用.太钢科技,2002,4:28-30
21张琥.攀钢轧机板形仪自动检测及闭环控制技术的应用与分析.四川冶金,2002,4:35-37
22魏立群,张杏耀,柳谋渊,等.1420 HC轧机板形控制的研究.钢铁,2003,38(9):30-34
23曹建国,顾云舟,张杰,等.1700冷轧带钢轧机板形控制能力研究.钢铁研究,2002,126(3):16-19
24邓辉,曹建国,张杰,等.多宽度无取向硅钢热轧板形控制特性研究.冶金设备,2008,167(1): 10-13
25曹建国,张杰,宋平.无取向硅钢热轧板形控制的ASR技术.钢铁,2006,41(6):43-46
26李爱东,郭雄飞高英,等.冷轧机高精度板形控制技术.有色金属,2005,4:35-36
27史华.冷轧板带机运行中的板形控制.鞍山师范学院学报,2005,7(2):41-43
28倪履安.冷轧精密不锈钢带的板形控制.轧钢,2009,26(1):71-74
29贾生晖,张杰,曹建国,等.冷连轧机硅钢板形控制目标的改进.北京科技大学学报,2002,24(3): 303-305
30程志彦.几种新型轧机的板形控制分析.机械管理开发,2005,85(4):36-37
31唐勤,董欣欣.唐钢超薄热带生产线板形控制.金属世界,2006,4:41-43
32 Liu Hongmin, Peng Yan, Chu Yupeng, Wang Yingrui. Strip element method for shape discrimination of strip rolling. Communications in Numerical Methods in Engineering, 2004, 20(9):709-720
33 Liu Hongmin, Zhang Xiuling, Wang Yingrui. Transfer matrix method of flatness control for strip mill. Journal of Materials Processing Technology, 2005,166(2):237-242
34 Liu Hongmin, He haitao, Shan Xiuying, et al. Flatness control based on dynamic effective matrix for cold strip mills. Chinese Journal of Mechanical Engineering, 2009.22(2):287-296
35 Peng Yan, Liu Hongmin, Wang Dongcheng. Simulation of type selection for 6-high cold tandem mill based on shape control ability. Journal of Central South University of Technology, 2007, 14(2): 278-284
36 Yan Peng, Dongcheng Wang. Simulation on profile control of a plate finishing rolling mill. Advanced Design and Manufacture to Gain a Competitive Edge. New Manufacturing Techniques and their Role in Improving Enterprise Performance, 2008,43-52
37 Yan Peng, Hongmin Liu, R. Du. A neural network-based shape control system for cold rolling operations. Journal of Materials Processing Technology, 2008: 202(1-3): 54-60
38 Peng Yan, Liu Hongmin.Study on increasing calculated precision and convergence speed of streamline strip element method.Journal of Central South of Technology, 2004,11(1):105-108
39 Peng Yan, Chu Yupeng, Liu Hongmin. Shape discrimination analysis of rolled strip based on strip element method. Journal of Iron And Steel Research(International), 2004, 11(1): 29-32
40 Yu Bingqiang, Liu Hongmin, Yang Lipo, etc.. A new type of contact shape meter and its industry application. International Conference on Measuring Technology and Mechatronics Automation (ICMTMA2009), 2009, 4:1058-1061
41 Li Zhiming, Peng Yan, Yu Bingqiang, etc.. A shape measurement system for cold-rolled steel strip based on DSP. 2009 WASE International Conference on Information Engineering,2009,2:257- 260
42 Yabo Sun, Hongmin Liu, Yan Peng. Influence of variation of the on_line shape of cold rolled strip on shape measuring and controlling system and its compensating measures. Proceedings ofSecond International Conference on Modelling and Simulation, 2009, 6: 212-219
43孙亚波,刘宏民,彭艳.板带轧制板形判别的降阶模型.工程力学,2009,26(12):204-210
44刘宏民,丁开荣,李兴东,等.板形标准曲线的理论计算方法.机械工程学报,2008,44(8):137-142
45刘宏民,于丙强,华仲新,等.分片压磁式板形仪.中国专利:ZL200610048380.1. 2006-9-29
46刘宏民,杨利坡,于丙强,等.整辊镶块式板形仪.中国专利: 200910075561.7
47刘佳伟,王军生,王鹏飞,等.冷轧机板形控制测量值处理方法.中国专利:200910011921.7
48王鹏飞,王军生,俞小峰,等.冷轧机变包角板形控制参数处理方法.中国专利:200910011920.2.
49刘宏民,彭艳,孙亚波.基于分布优化和影响因素补偿的板形标准曲线制定方法.中国专利:CN101543843
50刘宏民,王东城,彭艳,等.连轧机板形标准曲线计算方法.中国专利:CN101623707A
51刘宏民,彭艳,王东城,等.板形控制集成系统及执行方法.中国专利:CN101623708A
52尤磊.冷轧带钢板形检测辊的研究.[燕山大学工学硕士学位论文].2008:35-52
53胡晓明.准工业化气动板形检测仪的开发研究.[燕山大学工学硕士学位论文].2005,1-100
54杨敏.模糊控制与神经计算方法在板形控制中的应用.[北京工业大学工学硕士学位论文].2005,1-100
55陈丽.模糊神经网络及其在板形控制中的应用.[北京工业大学工学硕士学位论文].2005,1-100
56党凯.气动板形仪动态标定及板形控制性能研究.[燕山大学工学硕士学位论文].2008,1-100
57胡晓明.基于空气轴承的板形检测辊的研究设计.液压气动与密封,2006,6:10-13
58胡晓明.空气轴承式板形检测辊的研究设计.轻合金加工技术,2006,34(1):22-25
59何海涛. 900HC冷带轧机板形仪测控系统的研制.计算机测量与控制, 2003,11(7): 496-497
60何海涛.板形仪张力信号源的计算机模拟系统的研制.燕山大学学报,2002,26(4):322-324
61 Wang Junsheng, Jiang Zhengyi. A flying gauge change model in tandem cold strip mill. Journal of Materials Processing Technology, 2008, 204: 152-161
62赵启林,王军生,王国栋.一种板形检测值处理方法的开发及应用.材料与冶金学报, 2009,8(4):294-296
63王军生,白金兰,刘相华.带钢冷连轧原理与过程控制.北京:科学出版社, 2009
64单修迎,贾春玉,刘宏民.板带轧机板形控制倾辊弯辊神经模糊PID模型.机械工程学报,2009,45(9): 255-260
65贾春玉,单修迎.基于动态递归模糊神经网络的轧机辊缝动态辨识.塑性工程学报,2008,15(5):186-190
66贾春玉,单修迎,牛召平.自调整动态神经网络模型及其在带材板形预测中的应用.钢铁研究学报, 2006,18(12):50-53
67贾春玉,尚志东.冷轧板形目标曲线的补偿设定.钢铁研究学报,2000,8:64-67
68贾春玉,王建国.板带冷轧机高精度板形预测模型的研究.重型机械,2001,4:11-12
69贾春玉,于敏之,尚志东. HC轧机板形控制系统的设计.重型机械,2000,2:21-25
70贾春玉,王建国,李兴东,等.人工智能技术在板形控制中的应用.冶金设备,2003,140(3):8-13
71贾春玉.基于人工智能的自适应板形控制.钢铁研究学报,2001,13(4):58-61
72 Jia Chunyu, Shan Xiuying, Liu Hong-min, etc.. Fuzzy neural model for flatness pattern recognition. Journal of Iron and Steel Research (International), 2008, 15(6):33-38
73 Jia Chunyu, Shan Xiuying, Niu Zhaoping. High precision prediction of rolling force based on fuzzy and nerve for cold tandem mill. Journal of Iron and Steel Research (International), 2008, 15(2):23-27
74彭艳,刘宏民.HC轧机板形凸度控制策略的研究.钢铁,2002,37(4):35-38
75张秀玲,刘宏民.板形模式识别的GA-BP模型和改进的最小二乘法.钢铁,2003,38(10): 29-34
76张秀玲,陈丽杰,季颖,等.基于径向基函数神经网络的板形模式识别研究.工业仪表与自动化装置,2009,3:7-9
77张秀玲.冷带轧机板形智能识别与智能控制研究.[燕山大学工学博士学位论文].2002:25-60
78张秀玲,刘宏民.变结构神经网络在板形信号模式识别方面的应用.钢铁研究学报,2001,
13(2):62-66
79 Anon. Non-contact measurement of strip flatness. Steel Times International,2003,5(27):16-17
80孙一康.适用于轧钢过程的计算机控制系统.中国工程科学, 2000,2(1):73-76
81 Garcia Daniel, FGarcia Manuel, Obeso Faustino. Flatness measurement system based on a nonlinear optical triangulation technique. Transactions on Instrumentation and Measurement, 2002,2(51):188-195
82 Spreitzhofer Gunter, Duemmler Alfred, Trautwig Juergen. Contactless flatness measurement improves measurement quality in cold rolling mills. SEAISI Quarterly, 2003,1(32):43-50
83 Fischer Franz, Dieter Friedl, Nikolaus Andreas. A study on the buckling behaviour of strips and plates with residual stresses. Steel Research International, 2005,4(76):327-335
84 Agureev V.A, Kuryakin A V, Rudnev VS, etc.. Use of gage IP-4-gp to measure the flatness of strip on a hot-strip mill. Metallurgist, 2004,1(48):23-30
85 Lopez Carlos, Garcia Daniel F. Real time system for flatness inspection of steel strips. Proceedings of SPIE. The International Society for Optical Engineering2005, 2005:228-238
86 He Haitao, Li Nan. An RBF network approach to flatness pattern recognition based on SVM learning. Proceedings of the 2006 International Conference on Machine Learning and Cybernetics, ICMLC 2006, 2006: 2959-2962
87 Hong W.K, Choi J.J., Kim, J.S. etc.. Flatness adaptive control of a hot strip in finishing mills.Proceedings of the Institution of Mechanical Engineers, 2003, 9(217): 1243-1252
88 Wang Jian-Hui, Huang Min, Gu Shusheng. PSO-based decoupling PID control using wavelet neural network for strip flatness/gauge. Journal of Northeastern University, 2005,3(26):224-227
89 G?kdere Levent U., Benlyazid. A virtual prototype for a hybrid electric vehicle. Mechatronics, 2002, 12(12): 575-593
90 Amokrane S., Bouaskame, M.. Shape of the liquid-vapor coexistence curve for temperature and density dependent effective interactions. Physical Review E- Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics, 2002,65(51):1-10
91 Grossman Tovi, Balakrishnan Ravin, Sinqh Karan. An Interface for creating and manipulating curves using a high degree-of-freedom curve input device. Conference on Human Factors in Computing Systems-Proceedings, 2003:185-192
92邸洪双,张晓峰,刘相华,等.冷轧薄带板形检测信号正交多项式分解及数学模型.钢铁,1995, 3(9):33-36
93肖健华.智能模式识别方法.广州:华南理工出版社,2006:106-108
94王益群,尹国芳,孙旭光.板形信号模式识别方法的研究.机械工程学报,2003,39(8):91-94
95王益群,刘建,李连平.基于虚拟仪器的板形模式识别系统研究.中国机械工程,2008,19(3):
334-337
96王益群,刘涛,姜万录,等.冷连轧机工作辊温度场分析及膨胀量预报.中国机械工程.2006,17(5): 15-98
97 Wang Yiqun, Liu Jian, Ning Shurong, etc.. Hydraulic bend control system research of fuzzy self-adaptive PID based on virtual instrument. International Technology and Innovation Conference 2006, 2006:209-212
98 Wang Yiqun, Sun Xuguang, Liu Jian, etc. Application of smith predictor based on single neural network in cold rolling shape control. Chinese Journal of Mechanical Engineering, 2009,22(2): 282-286
99刘建,王益群,孙福,等.基于粒子群理论的板形模糊模式识别方法.机械工程学报, 2008.1(44): 173-178
100刘建,王益群,姜万录,等.引入单纯形算子的粒子群优化算法在板形模式识别中的应用.中国机械工程, 2007,18(23):2877-2880
101刘建,王益群,胡晓军,等.气动板形仪动态标定及系统圆周误差鉴相补偿.轧钢,2009,26(1): 26-29
102尹国芳,王益群,孙旭光.基于神经网络的板形信号模式识别方法的研究.中国机械工程,2004,15(24):15-18
103尹国芳.高精度铝箔板形测试系统的研究. [燕山大学工学博士学位论文]. 2006:65-70
104尹国芳,王益群,孙旭光.气动板形检测辊静态特性研究.液压与气动, 2004,8:28-30
105孙旭光,王益群,尹国芳.气动板形检测辊及其主要技术性能.钢铁研究学报,2006,18(12):47-49
106孙旭光,王益群,尹国芳,等.气动板形检测辊主要技术性能试验研究.自动化仪表, 2005,26(4):14-16
107孙旭光,胡晓明,李立丰.气动板形检测辊设计和气膜压力场数值求解.流体传动与控制,2004,4:13-15
108孙旭光.高精度气动板形仪研制与板形检测.[燕山大学博士后出站报告].2001:1-44
109杨铁林,孙旭光,王益群.分段式气动板形检测辊.机床与液压,2000,(4):58-62
110杨铁林.高精度气动板形仪基础技术的研究.[燕山大学工学博士学位论文].2001,11:49-52
111王启顺.空气轴承式板形仪的常见故障及其对策.轻合金加工技术,2003,31(7):13-16
112黄尚猛,李华川.空气轴承式板形仪检测轴承工作参数智能优化设计.冶金自动化,2008,1:267-270
113 Baumgartner U, Magele Ch, Renhart W. Pareto optimality and particle swarm optimization. IEEE Transactions on magnetics, 2004, 40(2):1172-1175
114彭开香,童朝南,董洁,等. 1400 mm铝带箔冷轧机板形控制系统.冶金自动化,2004,4(28):32-35
115贾生晖,尹晓青,曹建国,等.冷连轧机板形控制对策的仿真分析.冶金设备,2002,10(5):20-23
116王哲,邸洪双,王国栋,等.四辊轧机板形测控系统的设计.冶金自动化, 2002, 26(2): 34-37
117张清东,陈先霖,何安芮,等.冷轧宽带钢板形检测与自动控制.钢铁,1999, 34(10): 69-72
118张清东,吴越,瞿标,等.220冷连轧机板形控制性能综合改善.上海金属,2005,27(3):23-25
119穆炜,寇洪岩.本钢冷轧厂冷轧带钢板形控制和调节.鞍钢技术,2007, 334(2):42-44
120丁修堃.轧制过程自动化.北京:冶金工业出版社, 2005: 24-51
121王炎,孙一康.基于板形板厚综合控制目标函数的冷连轧机轧制参数智能优化新方法.冶金自动化,2002, 26(3): 11-14
122徐悦,柴天佑,毛志忠.四辊可逆冷轧机板形控制系统的研究.冶金自动化,1995, 19(1): 8-12
123华建新,金以慧,吴文斌.基于动态板形辊的冷轧板形控制新技术.钢铁, 2001,1:23-26
124 Mucke Gert, Gorgles Frank. Flatness measurement for high quality cold strip production. MPT Metallurgical Plant and Technology International, 2004,6: 40-45
125胡国栋,王琦,邹本友.磁弹变压器差动输出式冷轧带钢板形仪.钢铁,1994,29(4):56-59
126许石民,于丙强,胡国栋.应用于四辊可逆式冷轧机的压磁式冷轧带钢板形仪.冶金设备,2004,10:39-40
127安世奇,王京,孙一康.基于人工神经网络的板形缺陷识别.仪器仪表学报,2004,25(4):578-580
128刘青,王庆强,赵辉.高速无线传输在带钢板形检测中的应用.仪表技术与传感器,2008.12:83-84,92
129石燕,刘青.高速无线技术在带钢板形仪中的应用.电子测量技术,2008,31(8):103-105
130周莲莲,郑志刚,白振华.板带轧机板形检测设备系统误差综合补偿技术的开发.燕山大学学报,2009,33(3): 220-223
131林振波,连家创,刘宏民. ABB板形测量和控制系统及板形标准曲线.轧钢,1994,4:20-24
132王宏旭,连家创.四辊冷轧带材中张应力横向分布的求解.钢铁研究学报,1996,8(1):16-19
133刘翠波.1400 mm铝板冷轧机板形仪辊的清理.轻合金加工技术,2005,33(8): 33-34
134彭开香,童朝南,董洁,等.1400 mm铝带箔冷轧机板形控制系统.冶金自动化,2004,4:32- 35
135周津川. ABB板形仪的测量和控制系统在冷轧板材中的应用特点.天津冶金,2005,129:47-50
136陈炎,田原田越. ABB板形仪在攀钢HC冷连轧机的应用分析.冶金自动化,1999,3:48-50
137刘河桥.1850 mm冷轧机板形测量与控制系统分析.计算机与控制系统,2001,24(2):49-51
138高林林,陈玺. HC六辊轧机的板形调整特点分析研究.重型机械, 2006,增刊:5-8
139王仁忠,何安瑞,杨荃. LVC工作辊辊型的板形控制性能研究.钢铁, 2006,41(5):41-44
140段小勇.板带钢轧制时实现板形自动控制的条件.科技情报开发与经济,2002,12(2):145-146
141黄纶伟,陈先霖,张清东.板带冷轧机板形控制技术调控功效的比较研究.冶金设备, 2000,119 (1): 4-7
142王快社,王训宏,张兵,等.板形检测控制新方法.重型机械,2004,5:18-22
143郑岗,谢云鹏,刘丁,等.板形检测与板形控制方法.重型机械, 2002, 4:1-4
144孙蓟泉,周永红.板形控制技术及应用.鞍钢技术, 2006, 340(4):6-11
145黄贞益,李胜祗,孙中建,等.板形控制技术探讨.安徽工业大学学报,2002, 19(4): 273-277
146王文明,钟掘,谭建平.板形控制理论与技术进展.矿冶工程,2001,21(4):70-73
147胡贤磊,赵忠,王昭东,等.板形锁定法在轧制宽薄中厚板中的应用.钢铁,2005,40(1):47-50
148章彩云,谢东.ABB板形自动控制系统.铜陵学院学报,2009,2:64-66
149赵兴涛,田刚,沈振东.板形分段冷却的模糊控制.鞍钢技术,2009,355(1):39-41
150翟博,孙荣生,孙建林.板形控制技术在鞍钢冷连轧机组的应用.鞍钢技术,2009,355(1):49-52
151秋海滨,张明.板形控制新技术.有色金属加工.2009,38(3):24-29
152王志勇,郑德忠.板形模式软测量方法的研究.控制工程,2008,15(1):28-30
153王鹏飞,张殿华,刘佳伟,等.变包角板形测量值计算模型.钢铁研究学报, 2010,22(1):57-60
154张英明,白金兰.带材板形改善方法的研究进展.太原科技,2008,4:73-77
155张云鹏,王长松,张清东.基于效应函数的冷轧机板形闭环控制策略.北京科技大学学报,1999,21(2):195-197
156刘云峰.精细冷却在板形控制中的应用.梅山科技,2009,4:12-15
157郗安民,张宏昌,刘鸿飞,等.空气轴承式板形辊边部辊环标定新方法.冶金自动化,2009,33(2):57-59
158邸洪双,刘光明,蒋光炜.冷轧带钢板形模式识别方法概述.河南冶金,2009,17(4):1-6
159张雅琴,张小平,郭会光,等.冷轧带钢残余应力及其对板形影响的研究.塑性工程学报,2009, 16(5):75-79
160倪履安.冷轧精密不锈钢带的板形控制.轧钢, 2009,26(1):71-72
161杨立红,颜飞,马朝晖.汽车用预涂镀钢板的工艺和产品研发.钢铁, 2009,44(12):1-7
162马超,张国强,赵德华,等.弯辊对带钢板形影响的模拟研究.鞍钢技术,2009,395(5):36-39
163冯晓华,刘鹏,李静,等.一种改进的基于神经网络的板形缺陷识别方法.重型机械,2009,6:13-17
164丁志宇,魏博,谢建中.轧辊分段冷却技术在鞍钢1450板形控制中的应用.鞍钢技术,2009, 357(3):58-62
165张雪伟,王焱.智能识别方法在板形识别中的应用及发展趋势.钢铁研究学报,2010,22(1):1-3
166 Aaron K.R., Foster, N.L., Hazel, D.P., et al. Closed-loop position control system using LabVIEW. Proceedings IEEE,2002:283–286
167丁树峰,胡伟.轧制板带材的板形检测.机械设计与制造,2006,9:101-103
168郑廷才,司玉祥.辊式板形检测仪标定装置的试验研究.佳木斯工学院学报,1993,11(2):75-79
169何瑞安,张清东,许建勇,等.1800mm虚拟轧机板形控制性能.北京科技大学学报,2004,26(1): 91-84
170张清东,王文广,周晓.DSR宽带钢冷轧机的特殊板形控制性能.北京科技大学学报,2008,30(1): 71-76
171戴永彬,王冬梅,刘金辉,等.液压弯辊力板形控制系统的特性分析与仿真研究.辽宁工业大学学报(自然科学版),2008,28(4):220-223
172马静,黄景冬,商玉华,等.莱钢1500mm六辊可逆式冷轧机的板形控制技术.山东冶金,2008,30 (1):36-38
173郭同铀,周成,罗祯伟,等.韶钢宽板轧机板形控制实践.南方金属,2007,155(4):31-34
2王国栋.板形控制和板形理论.北京:冶金工业出版社,1986:1-20
3王国栋,刘相华,王军生.冷连轧生产工艺的进展.轧钢, 2003,20(1):37-41
4丁修堃.轧制过程自动化.北京:冶金工业出版社, 2005:206-210
5刘玠.冷轧生产自动化技术.北京:冶金工业出版社, 2006:95-105
6徐乐江.板带冷轧机板形控制与机型选择.北京:冶金工业出版社,2007:217-223
7庞玉华,钟春生,王经涛,等.冷轧带材板形检测计算机模拟研究.重型机械,2000,4:24-27
8王快社,赵远攀,钟春生.基于人工神经网络的一种板形检测方法研究.冶金设备,2002,134(4): 12-14
9庞玉华,钟春生,王经涛.基于子波理论的板形检测信号分析研究.金属成形工艺,2000,18(6): 7-9
10赵小燕,张朝晖,迟健男.基于张力测量的板形检测技术.制造业自动化,2007,29(3):90-92
11毛小春,杨西荣,钟春生.快速付里叶变换在板形检测中的应用.重型机械,2004,3:53-58
12庞玉华,毛晓春,钟春生.新型分段辊式动态板形检测仪.重型机械,1999,1:10-14
13庞玉华,钟春生,王经涛.轧钢板形检测仪研究动向.上海金属,2001,23(2):10-13
14王训宏,王快社,杨西荣,等.新型接触式板形检测辊的研制.冶金设备,2005,154(6):54-57
15钟春生,庞玉华,毛小春.板形检测方法研究趋向浅析.1998,6:1-5
16杨景明,王振臣.板形检测辊输出信号的通道处理方法.自动化仪表,1997,18(5):34-38
17张勇,李长江,何正春.计算机图像处理技术在钢板板形检测中的应用.重庆工业高等专科学校学报,2002,17(1):43-47
18白振华.冷连轧机高速生产过程核心工艺数学模型.北京:机械工业出版社,2009:1-95
19白振华,刘宏民,李秀军,等.平整轧制工艺模型.北京:冶金工业出版社,2010:1-20
20王清洁.板形仪控制技术在森吉米尔轧机上的应用.太钢科技,2002,4:28-30
21张琥.攀钢轧机板形仪自动检测及闭环控制技术的应用与分析.四川冶金,2002,4:35-37
22魏立群,张杏耀,柳谋渊,等.1420 HC轧机板形控制的研究.钢铁,2003,38(9):30-34
23曹建国,顾云舟,张杰,等.1700冷轧带钢轧机板形控制能力研究.钢铁研究,2002,126(3):16-19
24邓辉,曹建国,张杰,等.多宽度无取向硅钢热轧板形控制特性研究.冶金设备,2008,167(1): 10-13
25曹建国,张杰,宋平.无取向硅钢热轧板形控制的ASR技术.钢铁,2006,41(6):43-46
26李爱东,郭雄飞高英,等.冷轧机高精度板形控制技术.有色金属,2005,4:35-36
27史华.冷轧板带机运行中的板形控制.鞍山师范学院学报,2005,7(2):41-43
28倪履安.冷轧精密不锈钢带的板形控制.轧钢,2009,26(1):71-74
29贾生晖,张杰,曹建国,等.冷连轧机硅钢板形控制目标的改进.北京科技大学学报,2002,24(3): 303-305
30程志彦.几种新型轧机的板形控制分析.机械管理开发,2005,85(4):36-37
31唐勤,董欣欣.唐钢超薄热带生产线板形控制.金属世界,2006,4:41-43
32 Liu Hongmin, Peng Yan, Chu Yupeng, Wang Yingrui. Strip element method for shape discrimination of strip rolling. Communications in Numerical Methods in Engineering, 2004, 20(9):709-720
33 Liu Hongmin, Zhang Xiuling, Wang Yingrui. Transfer matrix method of flatness control for strip mill. Journal of Materials Processing Technology, 2005,166(2):237-242
34 Liu Hongmin, He haitao, Shan Xiuying, et al. Flatness control based on dynamic effective matrix for cold strip mills. Chinese Journal of Mechanical Engineering, 2009.22(2):287-296
35 Peng Yan, Liu Hongmin, Wang Dongcheng. Simulation of type selection for 6-high cold tandem mill based on shape control ability. Journal of Central South University of Technology, 2007, 14(2): 278-284
36 Yan Peng, Dongcheng Wang. Simulation on profile control of a plate finishing rolling mill. Advanced Design and Manufacture to Gain a Competitive Edge. New Manufacturing Techniques and their Role in Improving Enterprise Performance, 2008,43-52
37 Yan Peng, Hongmin Liu, R. Du. A neural network-based shape control system for cold rolling operations. Journal of Materials Processing Technology, 2008: 202(1-3): 54-60
38 Peng Yan, Liu Hongmin.Study on increasing calculated precision and convergence speed of streamline strip element method.Journal of Central South of Technology, 2004,11(1):105-108
39 Peng Yan, Chu Yupeng, Liu Hongmin. Shape discrimination analysis of rolled strip based on strip element method. Journal of Iron And Steel Research(International), 2004, 11(1): 29-32
40 Yu Bingqiang, Liu Hongmin, Yang Lipo, etc.. A new type of contact shape meter and its industry application. International Conference on Measuring Technology and Mechatronics Automation (ICMTMA2009), 2009, 4:1058-1061
41 Li Zhiming, Peng Yan, Yu Bingqiang, etc.. A shape measurement system for cold-rolled steel strip based on DSP. 2009 WASE International Conference on Information Engineering,2009,2:257- 260
42 Yabo Sun, Hongmin Liu, Yan Peng. Influence of variation of the on_line shape of cold rolled strip on shape measuring and controlling system and its compensating measures. Proceedings ofSecond International Conference on Modelling and Simulation, 2009, 6: 212-219
43孙亚波,刘宏民,彭艳.板带轧制板形判别的降阶模型.工程力学,2009,26(12):204-210
44刘宏民,丁开荣,李兴东,等.板形标准曲线的理论计算方法.机械工程学报,2008,44(8):137-142
45刘宏民,于丙强,华仲新,等.分片压磁式板形仪.中国专利:ZL200610048380.1. 2006-9-29
46刘宏民,杨利坡,于丙强,等.整辊镶块式板形仪.中国专利: 200910075561.7
47刘佳伟,王军生,王鹏飞,等.冷轧机板形控制测量值处理方法.中国专利:200910011921.7
48王鹏飞,王军生,俞小峰,等.冷轧机变包角板形控制参数处理方法.中国专利:200910011920.2.
49刘宏民,彭艳,孙亚波.基于分布优化和影响因素补偿的板形标准曲线制定方法.中国专利:CN101543843
50刘宏民,王东城,彭艳,等.连轧机板形标准曲线计算方法.中国专利:CN101623707A
51刘宏民,彭艳,王东城,等.板形控制集成系统及执行方法.中国专利:CN101623708A
52尤磊.冷轧带钢板形检测辊的研究.[燕山大学工学硕士学位论文].2008:35-52
53胡晓明.准工业化气动板形检测仪的开发研究.[燕山大学工学硕士学位论文].2005,1-100
54杨敏.模糊控制与神经计算方法在板形控制中的应用.[北京工业大学工学硕士学位论文].2005,1-100
55陈丽.模糊神经网络及其在板形控制中的应用.[北京工业大学工学硕士学位论文].2005,1-100
56党凯.气动板形仪动态标定及板形控制性能研究.[燕山大学工学硕士学位论文].2008,1-100
57胡晓明.基于空气轴承的板形检测辊的研究设计.液压气动与密封,2006,6:10-13
58胡晓明.空气轴承式板形检测辊的研究设计.轻合金加工技术,2006,34(1):22-25
59何海涛. 900HC冷带轧机板形仪测控系统的研制.计算机测量与控制, 2003,11(7): 496-497
60何海涛.板形仪张力信号源的计算机模拟系统的研制.燕山大学学报,2002,26(4):322-324
61 Wang Junsheng, Jiang Zhengyi. A flying gauge change model in tandem cold strip mill. Journal of Materials Processing Technology, 2008, 204: 152-161
62赵启林,王军生,王国栋.一种板形检测值处理方法的开发及应用.材料与冶金学报, 2009,8(4):294-296
63王军生,白金兰,刘相华.带钢冷连轧原理与过程控制.北京:科学出版社, 2009
64单修迎,贾春玉,刘宏民.板带轧机板形控制倾辊弯辊神经模糊PID模型.机械工程学报,2009,45(9): 255-260
65贾春玉,单修迎.基于动态递归模糊神经网络的轧机辊缝动态辨识.塑性工程学报,2008,15(5):186-190
66贾春玉,单修迎,牛召平.自调整动态神经网络模型及其在带材板形预测中的应用.钢铁研究学报, 2006,18(12):50-53
67贾春玉,尚志东.冷轧板形目标曲线的补偿设定.钢铁研究学报,2000,8:64-67
68贾春玉,王建国.板带冷轧机高精度板形预测模型的研究.重型机械,2001,4:11-12
69贾春玉,于敏之,尚志东. HC轧机板形控制系统的设计.重型机械,2000,2:21-25
70贾春玉,王建国,李兴东,等.人工智能技术在板形控制中的应用.冶金设备,2003,140(3):8-13
71贾春玉.基于人工智能的自适应板形控制.钢铁研究学报,2001,13(4):58-61
72 Jia Chunyu, Shan Xiuying, Liu Hong-min, etc.. Fuzzy neural model for flatness pattern recognition. Journal of Iron and Steel Research (International), 2008, 15(6):33-38
73 Jia Chunyu, Shan Xiuying, Niu Zhaoping. High precision prediction of rolling force based on fuzzy and nerve for cold tandem mill. Journal of Iron and Steel Research (International), 2008, 15(2):23-27
74彭艳,刘宏民.HC轧机板形凸度控制策略的研究.钢铁,2002,37(4):35-38
75张秀玲,刘宏民.板形模式识别的GA-BP模型和改进的最小二乘法.钢铁,2003,38(10): 29-34
76张秀玲,陈丽杰,季颖,等.基于径向基函数神经网络的板形模式识别研究.工业仪表与自动化装置,2009,3:7-9
77张秀玲.冷带轧机板形智能识别与智能控制研究.[燕山大学工学博士学位论文].2002:25-60
78张秀玲,刘宏民.变结构神经网络在板形信号模式识别方面的应用.钢铁研究学报,2001,
13(2):62-66
79 Anon. Non-contact measurement of strip flatness. Steel Times International,2003,5(27):16-17
80孙一康.适用于轧钢过程的计算机控制系统.中国工程科学, 2000,2(1):73-76
81 Garcia Daniel, FGarcia Manuel, Obeso Faustino. Flatness measurement system based on a nonlinear optical triangulation technique. Transactions on Instrumentation and Measurement, 2002,2(51):188-195
82 Spreitzhofer Gunter, Duemmler Alfred, Trautwig Juergen. Contactless flatness measurement improves measurement quality in cold rolling mills. SEAISI Quarterly, 2003,1(32):43-50
83 Fischer Franz, Dieter Friedl, Nikolaus Andreas. A study on the buckling behaviour of strips and plates with residual stresses. Steel Research International, 2005,4(76):327-335
84 Agureev V.A, Kuryakin A V, Rudnev VS, etc.. Use of gage IP-4-gp to measure the flatness of strip on a hot-strip mill. Metallurgist, 2004,1(48):23-30
85 Lopez Carlos, Garcia Daniel F. Real time system for flatness inspection of steel strips. Proceedings of SPIE. The International Society for Optical Engineering2005, 2005:228-238
86 He Haitao, Li Nan. An RBF network approach to flatness pattern recognition based on SVM learning. Proceedings of the 2006 International Conference on Machine Learning and Cybernetics, ICMLC 2006, 2006: 2959-2962
87 Hong W.K, Choi J.J., Kim, J.S. etc.. Flatness adaptive control of a hot strip in finishing mills.Proceedings of the Institution of Mechanical Engineers, 2003, 9(217): 1243-1252
88 Wang Jian-Hui, Huang Min, Gu Shusheng. PSO-based decoupling PID control using wavelet neural network for strip flatness/gauge. Journal of Northeastern University, 2005,3(26):224-227
89 G?kdere Levent U., Benlyazid. A virtual prototype for a hybrid electric vehicle. Mechatronics, 2002, 12(12): 575-593
90 Amokrane S., Bouaskame, M.. Shape of the liquid-vapor coexistence curve for temperature and density dependent effective interactions. Physical Review E- Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics, 2002,65(51):1-10
91 Grossman Tovi, Balakrishnan Ravin, Sinqh Karan. An Interface for creating and manipulating curves using a high degree-of-freedom curve input device. Conference on Human Factors in Computing Systems-Proceedings, 2003:185-192
92邸洪双,张晓峰,刘相华,等.冷轧薄带板形检测信号正交多项式分解及数学模型.钢铁,1995, 3(9):33-36
93肖健华.智能模式识别方法.广州:华南理工出版社,2006:106-108
94王益群,尹国芳,孙旭光.板形信号模式识别方法的研究.机械工程学报,2003,39(8):91-94
95王益群,刘建,李连平.基于虚拟仪器的板形模式识别系统研究.中国机械工程,2008,19(3):
334-337
96王益群,刘涛,姜万录,等.冷连轧机工作辊温度场分析及膨胀量预报.中国机械工程.2006,17(5): 15-98
97 Wang Yiqun, Liu Jian, Ning Shurong, etc.. Hydraulic bend control system research of fuzzy self-adaptive PID based on virtual instrument. International Technology and Innovation Conference 2006, 2006:209-212
98 Wang Yiqun, Sun Xuguang, Liu Jian, etc. Application of smith predictor based on single neural network in cold rolling shape control. Chinese Journal of Mechanical Engineering, 2009,22(2): 282-286
99刘建,王益群,孙福,等.基于粒子群理论的板形模糊模式识别方法.机械工程学报, 2008.1(44): 173-178
100刘建,王益群,姜万录,等.引入单纯形算子的粒子群优化算法在板形模式识别中的应用.中国机械工程, 2007,18(23):2877-2880
101刘建,王益群,胡晓军,等.气动板形仪动态标定及系统圆周误差鉴相补偿.轧钢,2009,26(1): 26-29
102尹国芳,王益群,孙旭光.基于神经网络的板形信号模式识别方法的研究.中国机械工程,2004,15(24):15-18
103尹国芳.高精度铝箔板形测试系统的研究. [燕山大学工学博士学位论文]. 2006:65-70
104尹国芳,王益群,孙旭光.气动板形检测辊静态特性研究.液压与气动, 2004,8:28-30
105孙旭光,王益群,尹国芳.气动板形检测辊及其主要技术性能.钢铁研究学报,2006,18(12):47-49
106孙旭光,王益群,尹国芳,等.气动板形检测辊主要技术性能试验研究.自动化仪表, 2005,26(4):14-16
107孙旭光,胡晓明,李立丰.气动板形检测辊设计和气膜压力场数值求解.流体传动与控制,2004,4:13-15
108孙旭光.高精度气动板形仪研制与板形检测.[燕山大学博士后出站报告].2001:1-44
109杨铁林,孙旭光,王益群.分段式气动板形检测辊.机床与液压,2000,(4):58-62
110杨铁林.高精度气动板形仪基础技术的研究.[燕山大学工学博士学位论文].2001,11:49-52
111王启顺.空气轴承式板形仪的常见故障及其对策.轻合金加工技术,2003,31(7):13-16
112黄尚猛,李华川.空气轴承式板形仪检测轴承工作参数智能优化设计.冶金自动化,2008,1:267-270
113 Baumgartner U, Magele Ch, Renhart W. Pareto optimality and particle swarm optimization. IEEE Transactions on magnetics, 2004, 40(2):1172-1175
114彭开香,童朝南,董洁,等. 1400 mm铝带箔冷轧机板形控制系统.冶金自动化,2004,4(28):32-35
115贾生晖,尹晓青,曹建国,等.冷连轧机板形控制对策的仿真分析.冶金设备,2002,10(5):20-23
116王哲,邸洪双,王国栋,等.四辊轧机板形测控系统的设计.冶金自动化, 2002, 26(2): 34-37
117张清东,陈先霖,何安芮,等.冷轧宽带钢板形检测与自动控制.钢铁,1999, 34(10): 69-72
118张清东,吴越,瞿标,等.220冷连轧机板形控制性能综合改善.上海金属,2005,27(3):23-25
119穆炜,寇洪岩.本钢冷轧厂冷轧带钢板形控制和调节.鞍钢技术,2007, 334(2):42-44
120丁修堃.轧制过程自动化.北京:冶金工业出版社, 2005: 24-51
121王炎,孙一康.基于板形板厚综合控制目标函数的冷连轧机轧制参数智能优化新方法.冶金自动化,2002, 26(3): 11-14
122徐悦,柴天佑,毛志忠.四辊可逆冷轧机板形控制系统的研究.冶金自动化,1995, 19(1): 8-12
123华建新,金以慧,吴文斌.基于动态板形辊的冷轧板形控制新技术.钢铁, 2001,1:23-26
124 Mucke Gert, Gorgles Frank. Flatness measurement for high quality cold strip production. MPT Metallurgical Plant and Technology International, 2004,6: 40-45
125胡国栋,王琦,邹本友.磁弹变压器差动输出式冷轧带钢板形仪.钢铁,1994,29(4):56-59
126许石民,于丙强,胡国栋.应用于四辊可逆式冷轧机的压磁式冷轧带钢板形仪.冶金设备,2004,10:39-40
127安世奇,王京,孙一康.基于人工神经网络的板形缺陷识别.仪器仪表学报,2004,25(4):578-580
128刘青,王庆强,赵辉.高速无线传输在带钢板形检测中的应用.仪表技术与传感器,2008.12:83-84,92
129石燕,刘青.高速无线技术在带钢板形仪中的应用.电子测量技术,2008,31(8):103-105
130周莲莲,郑志刚,白振华.板带轧机板形检测设备系统误差综合补偿技术的开发.燕山大学学报,2009,33(3): 220-223
131林振波,连家创,刘宏民. ABB板形测量和控制系统及板形标准曲线.轧钢,1994,4:20-24
132王宏旭,连家创.四辊冷轧带材中张应力横向分布的求解.钢铁研究学报,1996,8(1):16-19
133刘翠波.1400 mm铝板冷轧机板形仪辊的清理.轻合金加工技术,2005,33(8): 33-34
134彭开香,童朝南,董洁,等.1400 mm铝带箔冷轧机板形控制系统.冶金自动化,2004,4:32- 35
135周津川. ABB板形仪的测量和控制系统在冷轧板材中的应用特点.天津冶金,2005,129:47-50
136陈炎,田原田越. ABB板形仪在攀钢HC冷连轧机的应用分析.冶金自动化,1999,3:48-50
137刘河桥.1850 mm冷轧机板形测量与控制系统分析.计算机与控制系统,2001,24(2):49-51
138高林林,陈玺. HC六辊轧机的板形调整特点分析研究.重型机械, 2006,增刊:5-8
139王仁忠,何安瑞,杨荃. LVC工作辊辊型的板形控制性能研究.钢铁, 2006,41(5):41-44
140段小勇.板带钢轧制时实现板形自动控制的条件.科技情报开发与经济,2002,12(2):145-146
141黄纶伟,陈先霖,张清东.板带冷轧机板形控制技术调控功效的比较研究.冶金设备, 2000,119 (1): 4-7
142王快社,王训宏,张兵,等.板形检测控制新方法.重型机械,2004,5:18-22
143郑岗,谢云鹏,刘丁,等.板形检测与板形控制方法.重型机械, 2002, 4:1-4
144孙蓟泉,周永红.板形控制技术及应用.鞍钢技术, 2006, 340(4):6-11
145黄贞益,李胜祗,孙中建,等.板形控制技术探讨.安徽工业大学学报,2002, 19(4): 273-277
146王文明,钟掘,谭建平.板形控制理论与技术进展.矿冶工程,2001,21(4):70-73
147胡贤磊,赵忠,王昭东,等.板形锁定法在轧制宽薄中厚板中的应用.钢铁,2005,40(1):47-50
148章彩云,谢东.ABB板形自动控制系统.铜陵学院学报,2009,2:64-66
149赵兴涛,田刚,沈振东.板形分段冷却的模糊控制.鞍钢技术,2009,355(1):39-41
150翟博,孙荣生,孙建林.板形控制技术在鞍钢冷连轧机组的应用.鞍钢技术,2009,355(1):49-52
151秋海滨,张明.板形控制新技术.有色金属加工.2009,38(3):24-29
152王志勇,郑德忠.板形模式软测量方法的研究.控制工程,2008,15(1):28-30
153王鹏飞,张殿华,刘佳伟,等.变包角板形测量值计算模型.钢铁研究学报, 2010,22(1):57-60
154张英明,白金兰.带材板形改善方法的研究进展.太原科技,2008,4:73-77
155张云鹏,王长松,张清东.基于效应函数的冷轧机板形闭环控制策略.北京科技大学学报,1999,21(2):195-197
156刘云峰.精细冷却在板形控制中的应用.梅山科技,2009,4:12-15
157郗安民,张宏昌,刘鸿飞,等.空气轴承式板形辊边部辊环标定新方法.冶金自动化,2009,33(2):57-59
158邸洪双,刘光明,蒋光炜.冷轧带钢板形模式识别方法概述.河南冶金,2009,17(4):1-6
159张雅琴,张小平,郭会光,等.冷轧带钢残余应力及其对板形影响的研究.塑性工程学报,2009, 16(5):75-79
160倪履安.冷轧精密不锈钢带的板形控制.轧钢, 2009,26(1):71-72
161杨立红,颜飞,马朝晖.汽车用预涂镀钢板的工艺和产品研发.钢铁, 2009,44(12):1-7
162马超,张国强,赵德华,等.弯辊对带钢板形影响的模拟研究.鞍钢技术,2009,395(5):36-39
163冯晓华,刘鹏,李静,等.一种改进的基于神经网络的板形缺陷识别方法.重型机械,2009,6:13-17
164丁志宇,魏博,谢建中.轧辊分段冷却技术在鞍钢1450板形控制中的应用.鞍钢技术,2009, 357(3):58-62
165张雪伟,王焱.智能识别方法在板形识别中的应用及发展趋势.钢铁研究学报,2010,22(1):1-3
166 Aaron K.R., Foster, N.L., Hazel, D.P., et al. Closed-loop position control system using LabVIEW. Proceedings IEEE,2002:283–286
167丁树峰,胡伟.轧制板带材的板形检测.机械设计与制造,2006,9:101-103
168郑廷才,司玉祥.辊式板形检测仪标定装置的试验研究.佳木斯工学院学报,1993,11(2):75-79
169何瑞安,张清东,许建勇,等.1800mm虚拟轧机板形控制性能.北京科技大学学报,2004,26(1): 91-84
170张清东,王文广,周晓.DSR宽带钢冷轧机的特殊板形控制性能.北京科技大学学报,2008,30(1): 71-76
171戴永彬,王冬梅,刘金辉,等.液压弯辊力板形控制系统的特性分析与仿真研究.辽宁工业大学学报(自然科学版),2008,28(4):220-223
172马静,黄景冬,商玉华,等.莱钢1500mm六辊可逆式冷轧机的板形控制技术.山东冶金,2008,30 (1):36-38
173郭同铀,周成,罗祯伟,等.韶钢宽板轧机板形控制实践.南方金属,2007,155(4):31-34