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Identification and Correction of Errors in Analytical Models Using Test Data - Theoretical and Practical Bounds

机译:使用测试数据识别和校正分析模型中的错误 - 理论与实用界限

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The paper begins with a review of procedures for identifying error lacations in analytical (finite element) models using static and/or dynamic test data. A classification of possible error sources in an analytical model is then presented and their influence is discussed w.r. to the mass and stiffness matrices, the modal data and especially the error indicators used in the different localisation procedures. Bounds for error localisation are presented in this section. In order to derive practical bounds the influence of a typical measurement environment as given by incomplete and noisy test data on the error indicators is investigated. Using a simple academic bar example it is shown how modeling and measurement errors are superimposed. The limits for successful error localisation and subsequent model updating in presence of realistic test data are discussed.
机译:本文首先使用静态和/或动态测试数据识别分析(有限元)模型中的误差限制的程序审查。然后介绍了分析模型中可能的误差源的分类,并讨论了它们的影响。对质量和刚度矩阵,模态数据,尤其是在不同本地化过程中使用的错误指示符。在本节中介绍了错误本地化的界限。为了获得实际界限,调查了典型测量环境的影响,如错误指标对错误指标的不完整和嘈杂的测试数据给出。使用简单的学术条示例,显示了叠加建模和测量误差。讨论了成功错误定位和随后在现实测试数据的情况下更新的限制。

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