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含间隙RU-RPR解耦并联机构动力学建模及混沌现象辨识

Dynamics modeling and chaos identification of RU-RPR decoupled parallel mechanism with clearance
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摘要 为适应高速、重载、精密等工程需求,机构动力学特性及其蕴含的混沌现象日益引起重视。以自主提出的RURPR(R为转动副,U为虎克铰,P为移动副)两转动解耦并联机构为研究对象,针对运动副存在间隙状况,应用拉格朗日法建立间隙机构动力学方程,并采用Runge-Kutta(龙格-库塔)法予以求解;分析不同间隙大小对机构动态特性的影响,并借助相轨迹图、庞加莱(Poincare)截面映射法及李雅普诺夫(Lyapunov)指数进行机构混沌现象辨识。研究结果表明含间隙解耦并联机构动力学响应中存在混沌现象,并且随着间隙的增大,混沌现象愈加明显。所作工作是并联机构混沌动力学特性研究的有益尝试,对解耦并联机构动力学深入研究及进一步的样机研制与控制具有指导意义和实践价值。 In order to adapt to high speed, heavy load and precision engineering demand, the dynamic characteristics of the mechanism and contained chaotic phenomenon has become important increasingly. Taking a two rotational decoupled paral- lel mechanism RU-RPR (R stands for the revolute pair, U stands for the hooke joint, P stands for the prismatic pair) proposed independently as research object, the dynamics equation using the Lagrange method considering the clearance existing in the kinematic pair was established, and the equation by Runge-Kutta method was resolved. The effects of different clearance on the dynamic characteristics of the mechanism was analyzed. In addition, the chaos phenomenon in the dynamics behavior of the de- coupled parallel mechanism was identified with Phase track diagram, Poincare section mapping method and Lyapunov expo- nent, respectively. The results indicated that the chaos phenomenon exists in dynamic response of the decoupled parallel mech- anism with clearance, and the chaos phenomenon become more and more obvious with the increase of the clearance. The re- search content was a beneficial attempt for the research of the chaos phenomenon in parallel mechanism fields, and also possess theoretical guiding significance and practical application value for the further dynamics research, prototype development and control of the decoupled parallel mechanism.
出处 《机械设计》 CSCD 北大核心 2016年第2期24-29,共6页 Journal of Machine Design
基金 国家自然科学基金资助项目(51205339 51305384) 中国博士后科学基金资助项目(2013M541199)
关键词 并联机构 间隙 动力学 混沌辨识 LYAPUNOV指数 parallel mechanism clearance dynamics chaos identification Lyapunov exponent
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