热风回流焊机温度控制的软计算建模与系统设计
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摘要
热风回流焊机是表面贴装技术(SMI)中应用较广的表面贴装元器件的焊接设备之一。据权威机构预测,到2010年全球范围表面贴装元器件(SMC/SMD)的使用率将从目前的60%上升到90%,市场潜力非常巨大。而在热风回流焊机控制系统中,控温的准确和平稳是保持良好工艺的关键。
本文在已有的热风回流焊机控制系统的基础上,用集成度高、运行速度快的高速单片机取代以前的控制器,设计了一套可靠性好、扩展方便、兼容性强、功能齐全、操作简单、能完成复杂算法的软硬件监控系统。
同时,针对现行的智能PID加前馈的控制算法在大负荷经过时温度跌落较多、经过后温度超调太大的问题,从传热学角度建立了系统的静态模型,并对模型作了简化计算,详细分析了影响热能损耗的各类参数及影响力的大小。分析结果表明:该回流焊机中,两个强制通风口的设计极不合理,它的能耗占了总能耗的80%以上;其次,PCB板质量、环境温度、链条速度等参数也成为该机组热能消耗的主要影响因素。
为了更好的描述该温控系统的实时能量消耗情况,采用软计算方法,运用自适应神经模糊推理系统将PCB板质量、环境温度、链条速度作为输入,消耗热量作为输出,建立起三输入、一输出的动态系统模型,该模型借助神经网络的自学习能力对模型结构进行了优化,找到了较好的模型结构参数。仿真结果表明该模型是合适的。
The sirocco-circumfluence reflow soldering machine is one of the soldering devices which are used widely in surface mount technology.It is reported that the use of surface mount components or devices which is sixty percent has increase by ninety percent until 2010. The market is very potential.And in this control system the temperature exactness and stabilization is the key of good technics.On the base of primary sirocco-circumfluence reflow soldering system,this dissertation designs a set of monitoring control system with miro controller unit which has high speed and integration.The control syetem embeds hardware design and the relevant software design that can implement more complex algorithm.It is reassuring, compatible, convenient, multi-function and simple.At the same time, the present control mode of intelligent PID plus feedforward can not keep temperature from falling and rising when heavy load passes. In order to solve the problem,a static calorifics model of the system is built ,and every factors that consume the energy are analysed aboratively.The result shows that two coercive fans consume over eighty percent quantity of heat and printed circuit board, entironment temperature,chain speed are in the next place.Soft computing method is adopted to describe the heat consumption better.In adaptive neuro-fuzzy inference system, a dynamic calorifics model with three inputs and one output is completed to compute the consume quantity of heat.The model takes printed circuit board, entironment temperature,chain speed as inputs and consume quantity of heat as output. Self-teaching ability of neural network can optimize the model parameters and find appropriate parameters at the end.The simulation result has proved the model to be effective.
本文在已有的热风回流焊机控制系统的基础上,用集成度高、运行速度快的高速单片机取代以前的控制器,设计了一套可靠性好、扩展方便、兼容性强、功能齐全、操作简单、能完成复杂算法的软硬件监控系统。
同时,针对现行的智能PID加前馈的控制算法在大负荷经过时温度跌落较多、经过后温度超调太大的问题,从传热学角度建立了系统的静态模型,并对模型作了简化计算,详细分析了影响热能损耗的各类参数及影响力的大小。分析结果表明:该回流焊机中,两个强制通风口的设计极不合理,它的能耗占了总能耗的80%以上;其次,PCB板质量、环境温度、链条速度等参数也成为该机组热能消耗的主要影响因素。
为了更好的描述该温控系统的实时能量消耗情况,采用软计算方法,运用自适应神经模糊推理系统将PCB板质量、环境温度、链条速度作为输入,消耗热量作为输出,建立起三输入、一输出的动态系统模型,该模型借助神经网络的自学习能力对模型结构进行了优化,找到了较好的模型结构参数。仿真结果表明该模型是合适的。
The sirocco-circumfluence reflow soldering machine is one of the soldering devices which are used widely in surface mount technology.It is reported that the use of surface mount components or devices which is sixty percent has increase by ninety percent until 2010. The market is very potential.And in this control system the temperature exactness and stabilization is the key of good technics.On the base of primary sirocco-circumfluence reflow soldering system,this dissertation designs a set of monitoring control system with miro controller unit which has high speed and integration.The control syetem embeds hardware design and the relevant software design that can implement more complex algorithm.It is reassuring, compatible, convenient, multi-function and simple.At the same time, the present control mode of intelligent PID plus feedforward can not keep temperature from falling and rising when heavy load passes. In order to solve the problem,a static calorifics model of the system is built ,and every factors that consume the energy are analysed aboratively.The result shows that two coercive fans consume over eighty percent quantity of heat and printed circuit board, entironment temperature,chain speed are in the next place.Soft computing method is adopted to describe the heat consumption better.In adaptive neuro-fuzzy inference system, a dynamic calorifics model with three inputs and one output is completed to compute the consume quantity of heat.The model takes printed circuit board, entironment temperature,chain speed as inputs and consume quantity of heat as output. Self-teaching ability of neural network can optimize the model parameters and find appropriate parameters at the end.The simulation result has proved the model to be effective.
引文
[1] 傅清海,孙艳华,张家栋.软计算方法论及其住机电产品中的应用.黑龙江自动化技术与应用,1998,1:13
[2] 胡谋.“模糊逻辑.神经网络及软计算”专题导引.上海铁道大学学报,1996,2(7):1～2
[3] 李娟.浅议两种处理不确定性的软计算方法.甘肃科技,2000,16(2):38～39
[4] 盛兴华,赵俊慧.软计算及其新一代模糊控制器.北方交通大学学报,1999,4:15～17
[5] 董欣.控制理论的进展与交叉学科.山西高等学校社会科学学报,2003,15(1):48～49
[6] 孟伟.神经—模糊和软计算.电子科技,2001,11:24～25
[7] Dimirovski, G. M.; Yuanwei Jing. Towards hybrid soft computing approach to control of complex systems. 2002 First International IEEE Symposium 'Intelligent Systems' Proceedings. Piscataway: IEEE, 2002. 47～54
[8] Bosacchi, B.. Soft computing and electronic product engineering. Proceedings of the SPIE-The International Society for Optical Engineering, 1997, 3165: 48～57
[9] Gao, X. Z.. Comparison of conventional and soft computing-based power control methods in mobile communications systems. Soft Computing, 2001, 5 (4): 287
[10] Bosacchi, B.. On the role of soft computing in microelectronics technology. Soft Computing, 1997, 1(2): 57～60
[11] Ciftcioglu, O.. Data mining and soft computing. Management Information Systems, Data Mining Ⅲ, 2002, 6: 3～12
[12] Sterritt, R.. Autonomic computing: the natural fusion of soft computing and hard computing. SMC'03 Conference Proceedings. Piscataway: IEEE, 2003. 4754
[13] Ovaska, S. J.. Soft computing in industrial innovation: case study on home appliance technology. 2001 IEEE International Conference on Systems, Man and Cybernetics. e-Systems and e-Man for Cybernetics in Cyberspace. Piscataway: IEEE, 2001. 70
[14] Maione, G..; Naso, D.. A soft computing approach for task contracting in multi-agent manufacturing control. Computers in Industry, 2003, 52 (3): 199～219
[15] Jang, J. -S. R.; Jiuann-Jye Chen. Neuro-fuzzy and soft computing for speaker recognition. Proceedings of the Sixth IEEE International Conference on Fuzzy Systems. New York: IEEE, 1997. 663
[16] Yen, John; Lee, Bogj; Liao, J. C.. Soft computing approach to the metabolic modeling. Annual Conference of the North American Fuzzy Information Processing Society-NAFIPS, New Frontiers in Fuzzy Logic and Soft Computing. New York: IEEE, 1996. 343
[17] Jung-Bae Kim; Zeungnam Bien. Recognition of continuous Korean Sign Language using gesture tension model and soft computing technique. IEICE Transactions on Information and Systems, 2004, E87-D (5): 1265～1270
[18] Pal, S. K.. Soft computing tools and pattern recognition. IETE Journal of Research, 1998, 44 (1, 2); 61～88
[19] 蔡自兴,陈海燕,魏世勇.智能控制工程研究的进展.控制过程,2003,10(1):1～3
[20] 王平洋.电力系统自动化与智能技术.电力系统自动化,1998,22(1):6
[21] 周金宏,汪定伟.软计算求解分布式多工厂单件制造业的提前/拖期生产计划问题.控制理论和应用,2002,19(2):235～238
[22] 顾正彬等.软计算技术在热处理中的应用.金属热处理,2003,28(6):42～45
[23] 徐宝祥,郑荣,徐超.信息非确定系统确定类的软建模.情报科学,2002,20(4):78～80
[24] 孙丹,张秀艳.商业银行信用风险评估混合软计算系统.吉林大学学报(信息科学版),2002,20(3):428～430
[25] 姚建明,周国华.软计算方法在供应商选择多回合博弈过程中的应用.中国管理科学,2003,11(1):48～52
[26] 卢厚清等.软运筹学研究的回顾与展望.运筹与管理,2003,12(4):68～72
[27] 藩韬,赵卫东,盛昭瀚.粗分析在智能决策支持中的应用.管理工程学报,2001,15(3):8～11
[28] 谢克明,杨静.粗糙集理论及其在智能控制领域的应用前景.太原理工大学学报,1999,30(4):338
[29] 葛瑞.表面组装焊接技术的新发展.电子工艺技术,1999,20(1):33～34
[30] 盛菊仪,徐冠捷.无铅回流焊工艺及设备.电子工艺技术,2004,25(2):60
[31] 夏建亭.回流焊温度分布曲线图.电子工艺技术,1998,19(3):106～107
[32] 宋向辉.简析回流焊的温度曲线.情报指挥控制系统与仿真技术。2000年第6期。P48～49。
[33] 刘立新,李春龙,杨梅.基于新型高速高集成度单片机C8051F060的智能功率柜.国外电子元器件,2003,11:14～15
[34] 陈勇.带延迟复位功能的低压差稳压器IC.电子世界,1999,4
[35] 王武荣.AD594/AD595热电偶放大器及其应用.电测与仪表,1995,5:39～40
[36] 李敏,孟臣.单片K型热电偶放大与数字转换器MAX6675.单片机与嵌入式系统应用,2003,9:41～42。
[37] 刘立航.X25045芯片的原理及应用.中南民族学院学报,2001,20(2):49
[38] 张玉良.X25045可编程看门狗E2PROM与51系列单片机的接口.煤科总院常州自动化研究所.煤矿自动化:120～121
[39] 曹保根.一主从式RS485应用系统的设计与调试.电子技术,2000,2:44～45
[40] 赵毅,牟同升,沈小丽.单片机系统中数字滤波的算法.电测与仪表,2001,38(426):5
[41] 姜守达,吴昌盛,孙震.LabWindows/CVI多线程机制在数据采集中的应用.自动化技术与应用,2004,23(8):56
[42] 洪雪梅,郑立新,周凯汀.基于LabWindows/CVI的数字PID工程整定.福建电脑,2004,9:67
[43] 郑立新,周凯汀,龚勇,王永初.LabWindows/CVI与Matlab软接口技术及 应用.自动化仪表,2004,25(4):14
[44] 黄宗顺.SMD焊接温度曲线的探讨与分析.电子工艺技术.2003,24(1):16
[45] 陈宏芳,陆家钦主编.热工学.北京:中央广播电视大学出版社,1986.256
[46] 周筠清编.传热学.北京:冶金工业出版社,1989.1～3
[47] 倪春木等.模糊神经网络在小车摆系统辨识中的应用.厦门大学学报(自然科学版),2001,40(增刊1):102～104
[48] 彭玉楼,路秋静.基于自适应神经模糊推理系统的微波炉温度控制.陕西科技大学学报,2004,22(2):42
[49] 闻新等编著.MATLAB模糊逻辑工具箱的分析与应用.北京:科学出版社,2001.148～149
[50] 张智星,孙春在,水谷英二等(高春华等译).神经-模糊和软计算.西安:西安交通大学出版社,2000.238～240
[51] 张晓峰等.基于自适应模糊神经系统的热轧精轧机组动态设定系统.东北大学学报(自然科学版),2000,21(3):284。
[52] 丛爽,全钟华.神经-模糊建模平台的设计与应用.计算机工程,2002,28卷(9):8
[53] 岳玉芳,毛剑琴.一种基于T-S模型的快速自适应建模方法.控制与决策,2002,17(2):155
[2] 胡谋.“模糊逻辑.神经网络及软计算”专题导引.上海铁道大学学报,1996,2(7):1～2
[3] 李娟.浅议两种处理不确定性的软计算方法.甘肃科技,2000,16(2):38～39
[4] 盛兴华,赵俊慧.软计算及其新一代模糊控制器.北方交通大学学报,1999,4:15～17
[5] 董欣.控制理论的进展与交叉学科.山西高等学校社会科学学报,2003,15(1):48～49
[6] 孟伟.神经—模糊和软计算.电子科技,2001,11:24～25
[7] Dimirovski, G. M.; Yuanwei Jing. Towards hybrid soft computing approach to control of complex systems. 2002 First International IEEE Symposium 'Intelligent Systems' Proceedings. Piscataway: IEEE, 2002. 47～54
[8] Bosacchi, B.. Soft computing and electronic product engineering. Proceedings of the SPIE-The International Society for Optical Engineering, 1997, 3165: 48～57
[9] Gao, X. Z.. Comparison of conventional and soft computing-based power control methods in mobile communications systems. Soft Computing, 2001, 5 (4): 287
[10] Bosacchi, B.. On the role of soft computing in microelectronics technology. Soft Computing, 1997, 1(2): 57～60
[11] Ciftcioglu, O.. Data mining and soft computing. Management Information Systems, Data Mining Ⅲ, 2002, 6: 3～12
[12] Sterritt, R.. Autonomic computing: the natural fusion of soft computing and hard computing. SMC'03 Conference Proceedings. Piscataway: IEEE, 2003. 4754
[13] Ovaska, S. J.. Soft computing in industrial innovation: case study on home appliance technology. 2001 IEEE International Conference on Systems, Man and Cybernetics. e-Systems and e-Man for Cybernetics in Cyberspace. Piscataway: IEEE, 2001. 70
[14] Maione, G..; Naso, D.. A soft computing approach for task contracting in multi-agent manufacturing control. Computers in Industry, 2003, 52 (3): 199～219
[15] Jang, J. -S. R.; Jiuann-Jye Chen. Neuro-fuzzy and soft computing for speaker recognition. Proceedings of the Sixth IEEE International Conference on Fuzzy Systems. New York: IEEE, 1997. 663
[16] Yen, John; Lee, Bogj; Liao, J. C.. Soft computing approach to the metabolic modeling. Annual Conference of the North American Fuzzy Information Processing Society-NAFIPS, New Frontiers in Fuzzy Logic and Soft Computing. New York: IEEE, 1996. 343
[17] Jung-Bae Kim; Zeungnam Bien. Recognition of continuous Korean Sign Language using gesture tension model and soft computing technique. IEICE Transactions on Information and Systems, 2004, E87-D (5): 1265～1270
[18] Pal, S. K.. Soft computing tools and pattern recognition. IETE Journal of Research, 1998, 44 (1, 2); 61～88
[19] 蔡自兴,陈海燕,魏世勇.智能控制工程研究的进展.控制过程,2003,10(1):1～3
[20] 王平洋.电力系统自动化与智能技术.电力系统自动化,1998,22(1):6
[21] 周金宏,汪定伟.软计算求解分布式多工厂单件制造业的提前/拖期生产计划问题.控制理论和应用,2002,19(2):235～238
[22] 顾正彬等.软计算技术在热处理中的应用.金属热处理,2003,28(6):42～45
[23] 徐宝祥,郑荣,徐超.信息非确定系统确定类的软建模.情报科学,2002,20(4):78～80
[24] 孙丹,张秀艳.商业银行信用风险评估混合软计算系统.吉林大学学报(信息科学版),2002,20(3):428～430
[25] 姚建明,周国华.软计算方法在供应商选择多回合博弈过程中的应用.中国管理科学,2003,11(1):48～52
[26] 卢厚清等.软运筹学研究的回顾与展望.运筹与管理,2003,12(4):68～72
[27] 藩韬,赵卫东,盛昭瀚.粗分析在智能决策支持中的应用.管理工程学报,2001,15(3):8～11
[28] 谢克明,杨静.粗糙集理论及其在智能控制领域的应用前景.太原理工大学学报,1999,30(4):338
[29] 葛瑞.表面组装焊接技术的新发展.电子工艺技术,1999,20(1):33～34
[30] 盛菊仪,徐冠捷.无铅回流焊工艺及设备.电子工艺技术,2004,25(2):60
[31] 夏建亭.回流焊温度分布曲线图.电子工艺技术,1998,19(3):106～107
[32] 宋向辉.简析回流焊的温度曲线.情报指挥控制系统与仿真技术。2000年第6期。P48～49。
[33] 刘立新,李春龙,杨梅.基于新型高速高集成度单片机C8051F060的智能功率柜.国外电子元器件,2003,11:14～15
[34] 陈勇.带延迟复位功能的低压差稳压器IC.电子世界,1999,4
[35] 王武荣.AD594/AD595热电偶放大器及其应用.电测与仪表,1995,5:39～40
[36] 李敏,孟臣.单片K型热电偶放大与数字转换器MAX6675.单片机与嵌入式系统应用,2003,9:41～42。
[37] 刘立航.X25045芯片的原理及应用.中南民族学院学报,2001,20(2):49
[38] 张玉良.X25045可编程看门狗E2PROM与51系列单片机的接口.煤科总院常州自动化研究所.煤矿自动化:120～121
[39] 曹保根.一主从式RS485应用系统的设计与调试.电子技术,2000,2:44～45
[40] 赵毅,牟同升,沈小丽.单片机系统中数字滤波的算法.电测与仪表,2001,38(426):5
[41] 姜守达,吴昌盛,孙震.LabWindows/CVI多线程机制在数据采集中的应用.自动化技术与应用,2004,23(8):56
[42] 洪雪梅,郑立新,周凯汀.基于LabWindows/CVI的数字PID工程整定.福建电脑,2004,9:67
[43] 郑立新,周凯汀,龚勇,王永初.LabWindows/CVI与Matlab软接口技术及 应用.自动化仪表,2004,25(4):14
[44] 黄宗顺.SMD焊接温度曲线的探讨与分析.电子工艺技术.2003,24(1):16
[45] 陈宏芳,陆家钦主编.热工学.北京:中央广播电视大学出版社,1986.256
[46] 周筠清编.传热学.北京:冶金工业出版社,1989.1～3
[47] 倪春木等.模糊神经网络在小车摆系统辨识中的应用.厦门大学学报(自然科学版),2001,40(增刊1):102～104
[48] 彭玉楼,路秋静.基于自适应神经模糊推理系统的微波炉温度控制.陕西科技大学学报,2004,22(2):42
[49] 闻新等编著.MATLAB模糊逻辑工具箱的分析与应用.北京:科学出版社,2001.148～149
[50] 张智星,孙春在,水谷英二等(高春华等译).神经-模糊和软计算.西安:西安交通大学出版社,2000.238～240
[51] 张晓峰等.基于自适应模糊神经系统的热轧精轧机组动态设定系统.东北大学学报(自然科学版),2000,21(3):284。
[52] 丛爽,全钟华.神经-模糊建模平台的设计与应用.计算机工程,2002,28卷(9):8
[53] 岳玉芳,毛剑琴.一种基于T-S模型的快速自适应建模方法.控制与决策,2002,17(2):155