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跨声速风洞测力模型主动减振系统的试验研究
引用本文:陈卫东,邵敏强,杨兴华,路波,徐庆华.跨声速风洞测力模型主动减振系统的试验研究[J].振动工程学报,2007,20(1):91-96.
作者姓名:陈卫东  邵敏强  杨兴华  路波  徐庆华
作者单位:1. 南京航空航天大学航空宇航学院,江苏,南京,210016
2. 中国空气动力研究发展中心,四川,绵阳,621000
摘    要:跨声速风洞测力试验模型通常采取尾部支撑方式,构成的模型系统刚度较低。试验过程中,受气流脉动力的作用,模型在进入大攻角试验状态时,极易产生剧烈的低频振动,严重影响风洞测力试验的正常进行。针对跨声速风洞测力试验模型系统及其动力学特性,采用主动控制技术来实现风洞模型的振动抑制。建立了一套计算机实时主动减振系统;利用白行研制的、具有激振与减振双重功能的作动器来实施控制,作动器直接装载于模型的内结构空腔,不改变或破坏试验模型的外形结构;基于学习控制策略,提出了相应的控制律设计方法,并给出了一种简单、实用的控制算法;以内含实际支撑装置的风洞测力试验模型系统为对象,通过大量的地面试验评估了整个减振系统的性能。试验结果验证了该主动减振系统的可行性与有效性。

关 键 词:主动控制  减振  学习控制  风洞模型
文章编号:1004-4523(2007)01-0091-06
修稿时间:2006-04-19

Experimental evaluation of an active vibration control system for wind tunnel aerodynamic models
CHEN Wei-dong,SHAO Min-qiang,YANG Xing-hua,LU Bo,XU Qing-hua.Experimental evaluation of an active vibration control system for wind tunnel aerodynamic models[J].Journal of Vibration Engineering,2007,20(1):91-96.
Authors:CHEN Wei-dong  SHAO Min-qiang  YANG Xing-hua  LU Bo  XU Qing-hua
Abstract:This study presents an active vibration control(AVC)system that can significantly suppress dangerous low-frequency resonant vibration of the wind tunnel aerodynamic model at high angles of attack.A novel learning controller is proposed to increase the damping of the stiff-mounted model structures to minimize certain resonant responses.The corresponding control algorithm has a very simple structure which consists of two time-domain learning components in additive form: a fixed gain learning mechanism and a variable gain learning mechanism,both of that are all based on present and previous response information so that no a priori system modeling is required.The interactions between the learning components have been explored and they have been shown to be complementary to each other.The developed AVC system is experimentally examined by a practical wind tunnel aerodynamic model test system for near-resonant excitation cases.The experimental results indicate the effectiveness and feasibility of the presented AVC system,and the proposed controller is highly promising for this application field.
Keywords:active control  vibration reduction  learning control  wind tunnel aerodynamic model
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