石膏纤维板生产线厚度控制相关问题研究
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摘要
石膏纤维板是以石膏为主要原料,用纸纤维作增强材,经适量加水、加压、凝结干燥而制成的一种新型墙体材料,具有轻质、高效、防火、防潮、隔音、隔热等优点,近年来在国外已获得了高速的发展。在我国,随着建筑行业的迅猛发展,这种新型墙体材料也具有着广阔的市场和发展前景。
本文针对湖北三环墙体材料有限责任公司引进的国内第一条石膏纤维板生产线进行了研究,主要工作如下:
(1)通过对石膏纤维板生产线生产工艺的分析和研究,编制了工艺流程图。
(2)对生产线的PLC控制系统进行了设计,建立了控制系统三级网络结构图。
(3)对连续式压机工作原理和影响板厚的主要因素进行了分析。影响板厚的因素主要有:混和物料的木膏比、铺装机的铺料高度、连续式压机的速度以及压机主压辊压力等。
(4)对板厚控制问题进行了研究,利用人工神经网络技术建立了板厚控制模型。
(5)建立了基于改进遗传算法的神经网络厚度预测模型,利用误差均分变尺度搜索技术对网络训练算法进行了改进。结合模糊逻辑和神经网络的各自优势,建立了模糊神经网络厚度预测模型。
(6)对石膏纤维板厚度控制专家系统进行了初步设计,在WINDOWS XP操作系统平台下利用VB与MATLAB混合编程技术完成了部分应用程序的开发。
Gypsum fiber board (GFB) is a kind of artificial board using gypsum as main material and paper fibers as reinforcing material, it is made by adding proper water and pressure, solidifying and drying. As a kind of new building material, it has many advantages such as lightness, efficiency, fireproof, damp proof, insulate against sound and heat. It has gotten a fast development in foreign land lately. Due to the rapid development of architecture industry in our country, it will have a wide market and growing foreground.This paper makes a further study on the GFB product line in Hubei Sanhuan Wall Material Co., Ltd., which is the first line in china that imported from German. The major works in this paper include:1. The technics of GFB product line is studied, and the technics program is worked out.2. The PLC controlling system is studied and designed, the three level network structure of controlling system is established.3. The working principle of continuous pressing machine and the main factors that influenced the thickness of the board are analyzed. These factors are: the fiber-gypsum ratio, the layer height of material, the speed of continuous pressing machine and the pressure of main pressure rollers.4. Some problems of thickness controlling are studied, a thickness controlling model is established by using ANN on the base of analyzing the influenced factors.5. A ANN forecasting model based on new arithmetic and a FANN forecasting model combining the advantage of fuzzy logics and artificial neural networks are established.6. A preliminary study on the designing of the thickness controlling expert system in GFB product line is made, some programs and forms are developed by using vb and matlab.
本文针对湖北三环墙体材料有限责任公司引进的国内第一条石膏纤维板生产线进行了研究,主要工作如下:
(1)通过对石膏纤维板生产线生产工艺的分析和研究,编制了工艺流程图。
(2)对生产线的PLC控制系统进行了设计,建立了控制系统三级网络结构图。
(3)对连续式压机工作原理和影响板厚的主要因素进行了分析。影响板厚的因素主要有:混和物料的木膏比、铺装机的铺料高度、连续式压机的速度以及压机主压辊压力等。
(4)对板厚控制问题进行了研究,利用人工神经网络技术建立了板厚控制模型。
(5)建立了基于改进遗传算法的神经网络厚度预测模型,利用误差均分变尺度搜索技术对网络训练算法进行了改进。结合模糊逻辑和神经网络的各自优势,建立了模糊神经网络厚度预测模型。
(6)对石膏纤维板厚度控制专家系统进行了初步设计,在WINDOWS XP操作系统平台下利用VB与MATLAB混合编程技术完成了部分应用程序的开发。
Gypsum fiber board (GFB) is a kind of artificial board using gypsum as main material and paper fibers as reinforcing material, it is made by adding proper water and pressure, solidifying and drying. As a kind of new building material, it has many advantages such as lightness, efficiency, fireproof, damp proof, insulate against sound and heat. It has gotten a fast development in foreign land lately. Due to the rapid development of architecture industry in our country, it will have a wide market and growing foreground.This paper makes a further study on the GFB product line in Hubei Sanhuan Wall Material Co., Ltd., which is the first line in china that imported from German. The major works in this paper include:1. The technics of GFB product line is studied, and the technics program is worked out.2. The PLC controlling system is studied and designed, the three level network structure of controlling system is established.3. The working principle of continuous pressing machine and the main factors that influenced the thickness of the board are analyzed. These factors are: the fiber-gypsum ratio, the layer height of material, the speed of continuous pressing machine and the pressure of main pressure rollers.4. Some problems of thickness controlling are studied, a thickness controlling model is established by using ANN on the base of analyzing the influenced factors.5. A ANN forecasting model based on new arithmetic and a FANN forecasting model combining the advantage of fuzzy logics and artificial neural networks are established.6. A preliminary study on the designing of the thickness controlling expert system in GFB product line is made, some programs and forms are developed by using vb and matlab.
引文
[1] 陈福广,沈荣熹,徐洛屹.新型墙体材料手册.北京:中国建材工业出版社,2000
[2] 赵渠森编译.复合材料.北京:国防工业出版社,1985
[3] Egon fKraemer, Karsten H Lempfer. Gypsum Fiberboard History and Outlook. Inorganic Bonded Wood and Fiber Composite Materials. Forest Products Society(USA), 1991
[4] 蒋志全.均质石膏纤维板的生产与应用.房材与应用,1999.5
[5] 叶宪文.石膏纤维板在建筑上的应用.木材工业,2002,16(3):26-27
[6] 徐燮中.石膏纤维板生产工艺及设备简介.中国建材装备,1995.1
[7] 张宜生,陈士英,龙玲.半干法石膏纤维板工艺研究.木材工业,1998,12(5):8～11
[8] 常斗南.可编程序控制器原理、应用、试验.北京:机械工业出版社,1998
[9] 田瑞庭.可编程序控制器应用技术.北京:机械工业出版社,1994
[10] 白宏成,何晶晶,周建中.石膏板生产线计算机监控系统.中国建材科技.2000,3
[11] 廖常初.可编程序控制器应用技术.重庆:重庆大学出版社,1998
[12] 邱公伟.可编程控制器网络通信及应用.北京:清华大学出版社,2000
[13] Emst-Rudiger Olderog. Correct Real-Time Software for Programmable Logic Controllers. Lecture Notes in Computer Science 1999, 1999(1710)
[14] 连家创,刘宏民.板厚板形控制.北京:兵器工业出版社,1996
[15] H. Ford, J. M. Alexander. Advanced Mechanics of Materials, 1997
[16] 董军红.厚度控制方式的对比及应用.新疆有色金属,2001,2
[17] 刘兴华,韩继金.模糊控制的厚度计AGC.钢铁研究,2001,2
[18] 刘建昌.基于神经网络的自适应厚度控制.钢铁,1999,11
[19] 贾春玉.基于神经网络模糊推理的智能厚度控制.钢铁研究学报,2001,2
[20] 孙兆强.人工神经网络在冷轧机厚度、板形控制中的应用.天津冶金,1998,3
[21] 张颖,刘艳秋.软计算方法.北京:科学出版社,2002.
[22] 王小平,曹立明.遗传算法——理论、应用与软件实现.西安:西安交通大学出版社,2002
[23] 唐斌,凌旭峰,杨杰.基于GA的n维空间优化参数的搜索算法.系统仿真学报,2001,13(5):563～566
[24] 罗四维.遗传算法神经网络的学习方法.北方交通大学学报,1995,19(4):541～543
[25] 曹晓明,杨洁明.基于遗传优化的BP神经网络.机械管理开发,2004,2(77):66～67
[26] 卢洵.基于遗传算法的神经网络优化的研究.信息工程学院学报,1999,18(3):18～20
[27] 张兴会,刘玲.基于遗传算法的神经网络控制器.仪器仪表学报,2002,23(3):796～797
[28] 田旭光,宋彤,刘宇新.结合遗传算法优化BP神经网络的结构和参数.计算机应用于软件,2004,21(6):69～71
[29] 洪霞,马长山,谢宗安.基于遗传算法的神经网络权值优化.贵州工业大学学报,2003,32(6):48～51
[30] 曲惠杨,王清,马广富.一种基于遗传算法的神经网络控制方法.自动化技术与应用,2003,22(9):8～11
[31] Patrick K, Simson. Artificial Neural Systems-Foundations, Paradigms, Applications, and Implementations. Pergamon Press, 1990
[32] Widrow B et. al. Neural Networks, Application in Industry, Business and Science. Communication of the ACM, 37, 1994: 93～105
[33] Muhlenbein H. Evolutionary Algorithms: Theory and Applications. GMD Schloss Birlinboven, 1995
[34] 赵振宇,徐用懋.模糊理论和神经网络的基础与应用.北京:清华大学出版社,1996
[35] 王士同.模糊系统、模糊神经网络及应用程序设计.上海:上海科学技术文献出版社,1998
[36] 何铁军,黄卫.模糊神经网络在沥青路面使用性能评价中的应用.公路交通科技,2000,17(4):15～18
[37] 王铁生,华锡生。模糊神经网络在大坝变形预报中的应用.工程勘察,2002(5):56～58
[38] 杨长保,聂兰仕,孙鹏远.改进的模糊神经网络模型在储层产能预测中的应用研究.吉林大学学报(地球科学版),2003,33(1):48～50
[39] Donat J S, Bhat N, Mcavoy T J. Neural net based model predictive control. Int. J. control, 1991, 54(6): 1453～1468
[40] 尹朝庆,尹皓.人工智能与专家系统.北京:中国水利水电出版社,2001
[41] Takahara Y, Iljima J, Shiba N. A ModelManagement System and Its Implementafi_on Systems Science. 1996, 19(4): 33～36
[42] D. Y. Chen. Design and Implementation of Expert System Development tool ESDT—HKD, Cockpit Displays Ⅴⅲ: Displays for Defense Applications, SPIE. 2001, 4(3): 62
[43] D. Y. Chen. Scheduling and Reasoning of Tasks In Expert System De-velopment tool ESDT—HKD. Java/Jini Technologies and High—Performance Pervasive Computing. 2002, 7(2): 37～41
[44] Nilsson, N. J. Principles of Artificial Intelligence. Tioga publishing CO, 1980
[45] 王钦.Visual Basic 6.0入门与提高.北京:人民邮电出版社,2002
[46] 施阳,李俊,王惠刚等.MATLAB语言工具箱—TOOLBOX实用指南.西安:西北工业大学出版社,1998
[2] 赵渠森编译.复合材料.北京:国防工业出版社,1985
[3] Egon fKraemer, Karsten H Lempfer. Gypsum Fiberboard History and Outlook. Inorganic Bonded Wood and Fiber Composite Materials. Forest Products Society(USA), 1991
[4] 蒋志全.均质石膏纤维板的生产与应用.房材与应用,1999.5
[5] 叶宪文.石膏纤维板在建筑上的应用.木材工业,2002,16(3):26-27
[6] 徐燮中.石膏纤维板生产工艺及设备简介.中国建材装备,1995.1
[7] 张宜生,陈士英,龙玲.半干法石膏纤维板工艺研究.木材工业,1998,12(5):8～11
[8] 常斗南.可编程序控制器原理、应用、试验.北京:机械工业出版社,1998
[9] 田瑞庭.可编程序控制器应用技术.北京:机械工业出版社,1994
[10] 白宏成,何晶晶,周建中.石膏板生产线计算机监控系统.中国建材科技.2000,3
[11] 廖常初.可编程序控制器应用技术.重庆:重庆大学出版社,1998
[12] 邱公伟.可编程控制器网络通信及应用.北京:清华大学出版社,2000
[13] Emst-Rudiger Olderog. Correct Real-Time Software for Programmable Logic Controllers. Lecture Notes in Computer Science 1999, 1999(1710)
[14] 连家创,刘宏民.板厚板形控制.北京:兵器工业出版社,1996
[15] H. Ford, J. M. Alexander. Advanced Mechanics of Materials, 1997
[16] 董军红.厚度控制方式的对比及应用.新疆有色金属,2001,2
[17] 刘兴华,韩继金.模糊控制的厚度计AGC.钢铁研究,2001,2
[18] 刘建昌.基于神经网络的自适应厚度控制.钢铁,1999,11
[19] 贾春玉.基于神经网络模糊推理的智能厚度控制.钢铁研究学报,2001,2
[20] 孙兆强.人工神经网络在冷轧机厚度、板形控制中的应用.天津冶金,1998,3
[21] 张颖,刘艳秋.软计算方法.北京:科学出版社,2002.
[22] 王小平,曹立明.遗传算法——理论、应用与软件实现.西安:西安交通大学出版社,2002
[23] 唐斌,凌旭峰,杨杰.基于GA的n维空间优化参数的搜索算法.系统仿真学报,2001,13(5):563～566
[24] 罗四维.遗传算法神经网络的学习方法.北方交通大学学报,1995,19(4):541～543
[25] 曹晓明,杨洁明.基于遗传优化的BP神经网络.机械管理开发,2004,2(77):66～67
[26] 卢洵.基于遗传算法的神经网络优化的研究.信息工程学院学报,1999,18(3):18～20
[27] 张兴会,刘玲.基于遗传算法的神经网络控制器.仪器仪表学报,2002,23(3):796～797
[28] 田旭光,宋彤,刘宇新.结合遗传算法优化BP神经网络的结构和参数.计算机应用于软件,2004,21(6):69～71
[29] 洪霞,马长山,谢宗安.基于遗传算法的神经网络权值优化.贵州工业大学学报,2003,32(6):48～51
[30] 曲惠杨,王清,马广富.一种基于遗传算法的神经网络控制方法.自动化技术与应用,2003,22(9):8～11
[31] Patrick K, Simson. Artificial Neural Systems-Foundations, Paradigms, Applications, and Implementations. Pergamon Press, 1990
[32] Widrow B et. al. Neural Networks, Application in Industry, Business and Science. Communication of the ACM, 37, 1994: 93～105
[33] Muhlenbein H. Evolutionary Algorithms: Theory and Applications. GMD Schloss Birlinboven, 1995
[34] 赵振宇,徐用懋.模糊理论和神经网络的基础与应用.北京:清华大学出版社,1996
[35] 王士同.模糊系统、模糊神经网络及应用程序设计.上海:上海科学技术文献出版社,1998
[36] 何铁军,黄卫.模糊神经网络在沥青路面使用性能评价中的应用.公路交通科技,2000,17(4):15～18
[37] 王铁生,华锡生。模糊神经网络在大坝变形预报中的应用.工程勘察,2002(5):56～58
[38] 杨长保,聂兰仕,孙鹏远.改进的模糊神经网络模型在储层产能预测中的应用研究.吉林大学学报(地球科学版),2003,33(1):48～50
[39] Donat J S, Bhat N, Mcavoy T J. Neural net based model predictive control. Int. J. control, 1991, 54(6): 1453～1468
[40] 尹朝庆,尹皓.人工智能与专家系统.北京:中国水利水电出版社,2001
[41] Takahara Y, Iljima J, Shiba N. A ModelManagement System and Its Implementafi_on Systems Science. 1996, 19(4): 33～36
[42] D. Y. Chen. Design and Implementation of Expert System Development tool ESDT—HKD, Cockpit Displays Ⅴⅲ: Displays for Defense Applications, SPIE. 2001, 4(3): 62
[43] D. Y. Chen. Scheduling and Reasoning of Tasks In Expert System De-velopment tool ESDT—HKD. Java/Jini Technologies and High—Performance Pervasive Computing. 2002, 7(2): 37～41
[44] Nilsson, N. J. Principles of Artificial Intelligence. Tioga publishing CO, 1980
[45] 王钦.Visual Basic 6.0入门与提高.北京:人民邮电出版社,2002
[46] 施阳,李俊,王惠刚等.MATLAB语言工具箱—TOOLBOX实用指南.西安:西北工业大学出版社,1998