基于传递矩阵法的特征值敏感性分析

IF 3.4 Q1 ENGINEERING, MECHANICAL
Dieter Bestle
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引用次数: 3

摘要

对于线性机械系统,传递矩阵法是最有效的建模和分析方法之一。然而,与经典的建模策略不同,最终的特征值问题是基于一个矩阵,该矩阵是特征值的高度非线性函数。因此,经典的系统参数特征值敏感性分析策略不能适用。针对这种情况,本文提出了两种具体的策略,即直接微分策略和伴随变量法,特别是伴随变量法易于使用,适用于任意复杂的链或分支多体系统。与系统分析本身一样,它能够将整个系统的灵敏度分析分解为可解析确定的元素传递矩阵导数和递推公式,这些导数可以沿着拓扑图的传递路径应用。通过将结果与解析计算和数值微分比较,若干不同复杂度的实例验证了所提出的方法。所获得的程序可以通过提供精确的灵敏度来支持基于梯度的优化和稳健设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Eigenvalue sensitivity analysis based on the transfer matrix method

Eigenvalue sensitivity analysis based on the transfer matrix method

For linear mechanical systems, the transfer matrix method is one of the most efficient modeling and analysis methods. However, in contrast to classical modeling strategies, the final eigenvalue problem is based on a matrix which is a highly nonlinear function of the eigenvalues. Therefore, classical strategies for sensitivity analysis of eigenvalues w.r.t. system parameters cannot be applied. The paper develops two specific strategies for this situation, a direct differentiation strategy and an adjoint variable method, where especially the latter is easy to use and applicable to arbitrarily complex chain or branched multibody systems. Like the system analysis itself, it is able to break down the sensitivity analysis of the overall system to analytically determinable derivatives of element transfer matrices and recursive formula which can be applied along the transfer path of the topology figure. Several examples of different complexity validate the proposed approach by comparing results to analytical calculations and numerical differentiation. The obtained procedure may support gradient-based optimization and robust design by delivering exact sensitivities.

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