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ONLINE MATERIAL CHARACTERIZATION USING FULL-FIELD STRAIN MEASUREMENT

机译:使用全应变测量进行在线材料表征

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摘要

This paper presents and reviews an online methodology which characterizes materials using full-field strain measurement. The proposed methodology utilizes the principle of conservation of energy and formulates both the deterministic technique based on the pseudoinverse analysis and the stochastic technique based on the Kalman filter in terms of recursive linear equations. The methodology further describes the derivation the average Frobenius norm and the differential entropy as recursively computable measures enabling the evaluation of the well-posedness of the material characterization problem as well as the uncertainty of the identified constants. Comparative studies have identified that the deterministic identification is a particular case of the stochastic identification, whilst the adequacy and significance of both the average Frobenius norm and the differential entropy was reconfirmed.
机译:本文介绍并回顾了一种在线方法,该方法使用全场应变测量来表征材料。所提出的方法利用能量守恒原理,并根据递归线性方程式,提出了基于拟逆分析的确定性技术和基于卡尔曼滤波器的随机技术。该方法进一步描述了平均Frobenius范数和微分熵的推导,作为可递归计算的度量,可以评估材料表征问题的适定性以及所确定常数的不确定性。比较研究已经发现,确定性识别是随机识别的一个特例,而平均Frobenius范数和微分熵的充分性和重要性得到了再次确认。

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