期刊文献+

基于AMESim优化功能的参数识别法建模研究 被引量:6

Study on Modeling with Parameter Identification Method Based on Optimization Function of AMESim
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摘要 针对用AMESim建立系统模型时存在的问题,提出基于AMESim优化功能的参数识别建模方法。采用该方法建立某型注塑机注射回路的模型(使用AMESim软件的超级元件功能简化了模型),说明建模的详细步骤,重点阐述如何应用AMESim的优化功能识别系统的未知重要参数,以完善仿真模型。实验和仿真数据的对比说明,使用该方法建立的模型比较吻合真实模型。 Aiming at the existing problems of establishing system model based on AMESim, the modeling with parameter identification based on the optimization function of AMESim was put forward. The injection loop of an injection molding machine was modeled adopting the modeling method (the model was simplified by using the super-component function of AMESim), and the detailed steps of the modeling with the method were illustrated. How to use optimization function of AMESim to identify the system' s unknown important parameters was mainly expatiated in order to improve the simulation model. By comparing experiment data with simulation data, it shows that the model modeled with the method is more consistent with the actual model.
出处 《机床与液压》 北大核心 2011年第21期121-124,共4页 Machine Tool & Hydraulics
基金 国家自然科学基金项目(50705014) 广东省教育部产学研结合项目(2009A090100013)
关键词 AMESIM 优化功能 参数识别 超级元件 注射回路 建模 AMESim Optimization function Parameter identification Super component Injection loop Modeling
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  • 1H M.Paynter.Analysis and design of Engineering Systems[M].MIT Press,Cambridge,1961.
  • 2D C Karnopp,D L Margolis,R C Rosenberg.System Dynamics:A Unified Approach[M].New York,1990.

共引文献44

同被引文献49

  • 1秦家升,游善兰.AMESim软件的特征及其应用[J].工程机械,2004,35(12):6-8. 被引量:134
  • 2余佑官,龚国芳,胡国良.AMESim仿真技术及其在液压系统中的应用[J].液压气动与密封,2005,25(3):28-31. 被引量:281
  • 3姚荣康,朱昌明,詹永麒,周琼.带皮囊式蓄能器的油压缓冲器仿真与试验[J].系统仿真学报,2005,17(11):2741-2744. 被引量:7
  • 4黄中华,金波,刘少军,陈鹰.皮囊式蓄能器快速增压过程[J].中南大学学报(自然科学版),2006,37(2):306-310. 被引量:18
  • 5刘海丽,李华聪.液压机械系统建模仿真软件AMESim及其应用[J].机床与液压,2006,34(6):124-126. 被引量:96
  • 6MILLER J I, HENDERSON L M, CEBON D. Designing and testing an advanced pneumatic braking system for heavy vehicles[J]. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2013, 227(8): 1715-1729.
  • 7FRANK P M, KOPPEN-SELIGER B. New developments using AI in fault diagnosis[J]. Engineering Applications of Artificial Intelligence, 1997, 10(1)= 3 14.
  • 8PUGI L, PALAZZOLO A, FIORAVANTI D. Simulation of railway brake plants: an application to SAADKMS freight wagons[J]. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 2008, 222(4) 321-329.
  • 9CANTONE L, CRESCENTINI E, VERZICCOR R. A numerical model for the analysis of unsteady train braking and releasing manoeuvres[J]. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 2009, 223(3): 305-317.
  • 10ACARMAN T, OZGUNER U, HATIPOGLU C, et al. Pneumatic brake system modeling for systems analysis[C']// SAE International. Truck and Bus Meeting and Exposition. Warrendale: SAE International, 2000; 1-9.

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