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MATRIX DECOMPOSITION TECHNIQUES: USE AND LIMITATIONS IN MODAL ANALYSIS

机译:矩阵分解技术:模态分析中的使用和限制

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摘要

Many activities in modal analysis research and applications are classified under the general area of the inverse problem. Examples are modal parameter identification, parameter identification, finite element model updating and damage detection, among others. These type of problems usually result in a system of linear equations that are characterized by one or both of the following: (a)III conditioned system of equations, (b)Underdetermined system of equations. Matrix decomposition or factorization techniques can be extremely helpful in dealing with or detecting singularities and numerical ill conditioning. Among these methods are: (a)QR and QL algorithms, (b)LU factorization, (c)Chokesky decomposition, (d)Singular Value Decomposition. This paper is to introduce the theoretical grounds of these mathematical tools. Application of these techniques in modal analysis is illustrated and limitations and usefulness of solutions are emphasized.
机译:模态分析研究和应用中的许多活动都是在逆问题的一般领域进行分类。示例是模态参数识别,参数识别,有限元模型更新和损坏检测等。这些类型的问题通常导致线性方程的系统,其特征在于以下一个或两个:(a)III条件的等式系统,(b)未确定的等式系统。矩阵分解或分解技术在处理或检测奇点和数值下调方面非常有用。这些方法包括:(a)QR和QL算法,(b)Lu分解,(c)冲击孔分解,(d)奇异值分解。本文介绍了这些数学工具的理论应。说明了这些技术在模态分析中的应用,并强调了解决方案的限制和有用性。

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