动态称重技术的研究
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摘要
称重与现代生产生活息息相关、紧密相连，是计量的一个重要分支，自古以来就受到人们的重视。称重分为静态称重和动态称重，日常生活中经常遇到的是静态称重，然而在实际生产中，例如流水线生产、食品加工、医药生产、生产计量、交通运输等大多涉及的是动态称重。因为动态称重可以缩短作业时间、改善操作条件、提高生产效率和加强企业管理，从而推进了工业生产的自动化和管理的现代化。因此，动态称重系统的研究在国民经济中具有重要意义。
本文阐述了系统的结构和工作原理，对动态称重系统进行了分析，搭建了硬件系统，并研制了称重软件系统。动态称重系统以计算机为核心，通过称重传感器将物料的多少感测出来，经过信号调理电路，送入数据采集卡，计算机再进行采集。本文还分析了系统的动态特性，建立了系统的数学模型，利用数字滤波技术对采集到的信号进行了处理，并根据系统是一个典型的自回归滑动平均(ARMA)模型，将动态称重问题转化为一个参数辨识和参数估计的问题，基于最小二乘法原理的渐消记忆和限定记忆法相结合，采用了带有遗忘因子的限定记忆法，该方法具有精度高、数值稳定好、运算量少等特点。本系统软件以Windows98为平台，在可视化快速应用程序开发环境C++Builder下编制。并利用硬件定时的方法解决了Windows98环境下定时采样的难题。
实验结果表明，该系统的设计是可行的，具有较好的实时性和可靠性，有一定的实用价值和推广前景。
Weighing is closely related to modern production and lives, and is an important branch of measurement. Importance has been attached to weighing since antiquity. Weighing can be divided into two sorts: static weighing and dynamic weighing. In daily life, people usually use static weighing, nevertheless in practical production such as pipelining production, food processing, medicine production, production measurement, transport and communication trade etc. mostly use dynamic weighing. Because dynamic weighing can shorten job time, improve operating condition, increase production efficiency, intensify business management, and consequently push the automation of industrial production and modernization of management. Hence, dynamic weighing plays an important role in national economy.
The structure and operating principle of the system are expatiated, dynamic weighing system is analyzed, the hardware system is established and the software system is developed. Dynamic weighing system centers on computer. The amount of material is sensed by weighing sensor, adjusted by signal adjusting circuit, sent to data acquisition card, and finally acquired by computer. Moreover, dynamic characteristic of the system is analyzed, and the mathematic model is built. The weighing signal acquired is processed through digital filter. According to the system being a typical autoregressive moving average (ARMA) model, dynamic weighing problem is converted into parameter identification and parameter estimation problem, regression memory and restricted memory methods which are based on least squares methods are synthesized, and the restricted memory method with forgetting factor is adopted, which has the advantages of high precision, fine numerical stability, few calculations etc. The system software is based on Windows98 and developed under visual rapid application development environment C++Builder. At the same time, the difficult problem of timing data acquisition under Windows98 is solved through hardware timing.
Experimental results indicate that the design of this system is feasible, and the system not only has good real-time characteristic and reliability, but also has practical value and popularizing prospect.
本文阐述了系统的结构和工作原理，对动态称重系统进行了分析，搭建了硬件系统，并研制了称重软件系统。动态称重系统以计算机为核心，通过称重传感器将物料的多少感测出来，经过信号调理电路，送入数据采集卡，计算机再进行采集。本文还分析了系统的动态特性，建立了系统的数学模型，利用数字滤波技术对采集到的信号进行了处理，并根据系统是一个典型的自回归滑动平均(ARMA)模型，将动态称重问题转化为一个参数辨识和参数估计的问题，基于最小二乘法原理的渐消记忆和限定记忆法相结合，采用了带有遗忘因子的限定记忆法，该方法具有精度高、数值稳定好、运算量少等特点。本系统软件以Windows98为平台，在可视化快速应用程序开发环境C++Builder下编制。并利用硬件定时的方法解决了Windows98环境下定时采样的难题。
实验结果表明，该系统的设计是可行的，具有较好的实时性和可靠性，有一定的实用价值和推广前景。
Weighing is closely related to modern production and lives, and is an important branch of measurement. Importance has been attached to weighing since antiquity. Weighing can be divided into two sorts: static weighing and dynamic weighing. In daily life, people usually use static weighing, nevertheless in practical production such as pipelining production, food processing, medicine production, production measurement, transport and communication trade etc. mostly use dynamic weighing. Because dynamic weighing can shorten job time, improve operating condition, increase production efficiency, intensify business management, and consequently push the automation of industrial production and modernization of management. Hence, dynamic weighing plays an important role in national economy.
The structure and operating principle of the system are expatiated, dynamic weighing system is analyzed, the hardware system is established and the software system is developed. Dynamic weighing system centers on computer. The amount of material is sensed by weighing sensor, adjusted by signal adjusting circuit, sent to data acquisition card, and finally acquired by computer. Moreover, dynamic characteristic of the system is analyzed, and the mathematic model is built. The weighing signal acquired is processed through digital filter. According to the system being a typical autoregressive moving average (ARMA) model, dynamic weighing problem is converted into parameter identification and parameter estimation problem, regression memory and restricted memory methods which are based on least squares methods are synthesized, and the restricted memory method with forgetting factor is adopted, which has the advantages of high precision, fine numerical stability, few calculations etc. The system software is based on Windows98 and developed under visual rapid application development environment C++Builder. At the same time, the difficult problem of timing data acquisition under Windows98 is solved through hardware timing.
Experimental results indicate that the design of this system is feasible, and the system not only has good real-time characteristic and reliability, but also has practical value and popularizing prospect.
引文
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[3] 施昌彦．动态称重测力技术的现状和发展动向．计量与测试技术[J]．2000(01)：18～20
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[20] 任志斌．电阻式应变称重传感器选用与使用原则浅谈．衡器[J]．2005(01)．32～33
[21] 王琦．电阻应变式称重传感器的设计．木材加工机械[J]．2005(03)：20～30
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[32] 孟晓风，王行仁，黄俊钦．最小二乘估计的HOUSEHOLDER变换快速递推算法．自动化学报[J]．1994，20(1)：20～28
[33] H.Robertson, T.Perera. Feasibility for Automatic Data Collection. Simulation Conference[C]. 2001,(2): 984～990
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[36] 胡士强，张云松，张小英．基于C++Builder的实时测控软件．仪器仪表用户[J]．2001，8(6)：39～42
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[45] Anthony Zaknich. An Integrated Sensory-Intelligent System for Underwater Acoustic Signal-processing Applications. IEEE Journal of Oceanic Engineering[C]. Vol.28, NO.4, October 2003. 750～759
[46] W. Balachandran, Y. M. Enab, M. Halimic, M. Tariq. Intelligent robot based dynamic weighing system. Proceedings of SPIE, The International Society for Optical Engineering[C]. 1994, 2353: 398-409
[47] 胡寿松．自动控制原理[M]．国防工业出版社．1994
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[2] 陆伯勤．电子称重技术和自动称重系统的进展．自动化博览[J]．1999(01)：1～6
[3] 施昌彦．动态称重测力技术的现状和发展动向．计量与测试技术[J]．2000(01)：18～20
[4] 郭玉峰．不停车收费系统中的不停车称重[D]．河南：郑州大学，2005
[5] 陈江浩．动态称重与自动配料系统的研究与开发[D]．甘肃：兰州大学，2003
[6] 施昌彦．测力称重计量的某些发展动向．现代计量测试[J]．1994(6)：2～5
[7] Wei-Qun Shu. Dynamic Weighing Under Nonzero Initial Conditions. IEEE Transcation on Instrument and Measurement[J]. 1993, 42(4): 806～811
[8] 贺曙新．车辆动态称重技术的历史、现状与展望．中外公路[J]．2004，24(6)：104～108
[9] 徐科军，江敦明．称重传感器自适应动态补偿方法．仪表技术与传感器[J]．1997(6)：6～8
[10] 张海清，李宝安，罗先和．定量下料问题的动态称重解决方案．计量学报[J]．1998，19(3)：221～224
[11] 杨玉．动态称重及其数据处理．湖南轻工业高等专科学校学报[J]．2001，3(3)：15～18
[12] 李宝安，李行善，罗先和．动态称重系统计量误差的动态校正．仪器仪表学报[J]．2001，22(3)：251～246
[13] Dick Johnson. Weighing technology can be pretty heavy stuff. Control Engineering. Mar 2000, 47(3): 90～92
[14] 宋爽，宋惠改，於亮．动态称重技术的应用与展望．河北冶金[J]．2000(3)：30～56
[15] 康茜．用于动态称重的一种数据处理方法．测量与检修[J]．1997，17(3)：22～43
[16] Toshiro ONO. On Dynamic Weighing of Highway Vehicles in Motion. SICE Annual Conference in Fukui[C]. August 2003: 2109～2115
[17] 殳伟群．基于参数估计的动态称重新方法．北京：计量学报[J]．1993，14(2)：149～153
[18] 杨廷华．微机控制自动称重系统．自动化与仪表[J]．2001(02)：56～57
[19] 凌杰．公路动态称重系统的设计理论研究[D]．西安：长安大学，2001．
[20] 任志斌．电阻式应变称重传感器选用与使用原则浅谈．衡器[J]．2005(01)．32～33
[21] 王琦．电阻应变式称重传感器的设计．木材加工机械[J]．2005(03)：20～30
[22] 刘海涛．Borland C++ Builder入门与提高[M]．清华大学出版社，2000
[23] 杨叔子，杨克冲．机械工程控制基础[M]．华中科技大学出版社 1984
[24] 姜建国，曹建中，高玉明．信号与系统分析基础[M]．清华大学出版社．1994
[25] R. Engel. Dynamic Weighing-Improvements in Gravimetric Liquid Flowmeter Calibration. The 5th International Symposium on Fluid Flow Measurement[C]. April 8-10, 2002, 1～14
[26] 徐南荣，宋文忠，夏安邦．系统辨识[M]．东南大学出版社．1991
[27] 张国雄，金篆芷．测控电路[M]，机械工业出版社．2001
[28] 黄俊钦．测试系统动力学[M]．国防工业出版社，1996
[29] 刘整社．时变参数的一种快速跟踪最小二乘估计方法．控制理论与应用[J]．1995，12(2)：260～264
[30] 肖耕亚，陈列平．系统辨识中的限定记忆最小二乘法参数估计算法及应用．韶关大学学报(自然科学版)[J]．1998，19(6)：33～39
[31] 陈显枝，陈冲．基于最小二乘改进算法的时变系统参数辨识．福州大学学报(自然科学版)[J]．2005，Vol．33(2)：163～166
[32] 孟晓风，王行仁，黄俊钦．最小二乘估计的HOUSEHOLDER变换快速递推算法．自动化学报[J]．1994，20(1)：20～28
[33] H.Robertson, T.Perera. Feasibility for Automatic Data Collection. Simulation Conference[C]. 2001,(2): 984～990
[34] PCL-812PG PCL-818HG/L Enhanced Multi-function Data Acquisition Card, EVOC Technology Co., Ltd, 2000
[35] 周纪卿，朱因远．非线性振动[M]．西安交通大学出版社．1998
[36] 胡士强，张云松，张小英．基于C++Builder的实时测控软件．仪器仪表用户[J]．2001，8(6)：39～42
[37] 徐宁寿．系统辨识技术及其应用[M]．机械工业出版社．1986
[38] 任锦堂．系统辨识[M]．上海交通大学出版社．1989
[39] Gao Zonghai, Mao Jiandong. Dynamic Weighing Technology Combing Parameter Identification. 3rd International Symposium on Instrumentation Science and Technology[C], 2004: 367～371
[40] L．雍，T．索德斯图姆．递推辨识的理论与实践[M]．科学出版社．1989
[41] 黄俊饮．测试误差分析与数学模型[M]．国防工业出版社．1985
[42] Mirodlav D．Lutovac，Dejan V．Tosic，Brian L．Evans，朱义胜，董辉译．信号处理滤波器设计[M]．电子工业出版社．2004
[43] 夏天昌．系统辨识-最小二乘法[M]．国防工业出版社．1984
[44] 施昌彦，朱鼎铭，陈贻管．测量与称重技术论文选[C]．计量出版社．1982
[45] Anthony Zaknich. An Integrated Sensory-Intelligent System for Underwater Acoustic Signal-processing Applications. IEEE Journal of Oceanic Engineering[C]. Vol.28, NO.4, October 2003. 750～759
[46] W. Balachandran, Y. M. Enab, M. Halimic, M. Tariq. Intelligent robot based dynamic weighing system. Proceedings of SPIE, The International Society for Optical Engineering[C]. 1994, 2353: 398-409
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