基于Chebyshev多项式和有限质点法的Bennett机构动力响应不确定性分析

DYNAMICS ANALYSIS OF BENNETT LINKAGE WITH PARAMETER UNCERTAINTIES USING CHEBYSHEV POLYNOMIALS METHOD AND FINITE PARTICLE METHOD

  • 摘要: Bennett机构在建筑、航天、机械等领域有广阔的应用前景。在实际应用中机构参数等具有不确定性,需要在动力分析中考虑其影响。本文提出了一种基于Chebyshev多项式和有限质点法的Bennett机构动力响应不确定性分析方法。首先介绍了Bennett机构的有限质点法建模及分析方法;然后引入Chebyshev多项式,建立机构参数与动力响应之间的关系,并通过区间运算得到系统动态响应的边界,提出了一种易与有限质点法结合的不确定性分析非侵入式算法;通过算例验证了方法的有效性,并开展了Bennett机构动力响应不确定性分析。分析结果表明,连杆长度不确定性对机构位移和速度有较大影响,位移上下边界最大差值占确定参数模型的87.1%;连杆弹性模量不确定性对机构位移影响较小,对速度、连杆应变能影响较大,速度上下边界最大差值占确定参数模型的277.0%;同时碰撞等强外部作用会显著增强不确定性参数的影响。

     

    Abstract: Bennett linkage in engineering may contain uncertain parameters, and the influence of uncertain parameters need to be considered in its dynamic analysis. In this study, a dynamic analysis method is proposed for Bennett linkage with parameter uncertainties based on Chebyshev polynomials method and finite particle method (FPM). Firstly, the modeling method of Bennett linkage and the corresponding elements of FPM are presented. Subsequently, by introducing Chebyshev polynomials method, the dependence of the system dynamic response on its parameters is established, and the boundaries of dynamic response can be obtained through interval operations. A non-intrusive uncertainty analysis method that can be easily integrated with the FPM is proposed. Finally, the effectiveness of the method proposed is validated by the numerical examples, and the dynamic analysis of Bennett linkage with parameter uncertainties is conducted. The analysis results indicate that the uncertainty in link lengths significantly influences both the displacement response and velocity response of Bennett linkage. The maximum difference between upper and lower displacement boundaries accounts for 87.1% of that of the deterministic parameter model at that particular time. The uncertainty in Young’s modulus of link has a minor impact on the displacement of Bennett linkage but a substantial impact on the velocity and potential energy of link. The maximum difference between upper and lower velocity boundaries accounts for 277.0% of that of the deterministic parameter model at that particular time. Strong external forces, such as the contact between adjacent links, can significantly enhance the influence of uncertain parameters.

     

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