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Uncertainty quantification in structural damage diagnosis

机译:结构损伤诊断中的不确定性量化

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This paper develops methods for the quantification of uncertainty in each of the three steps of damage diagnosis (detection, localization and quantification), in the context of continuous online monitoring. A model-based approach is used for diagnosis. Sources of uncertainty include physical variability, measurement uncertainty and model errors. Damage detection is based on residuals between nominal and damaged system-level responses, using statistical hypothesis testing whose uncertainty can be captured easily. Localization is based on the comparison of damage signatures derived from the system model. A metric based on least squares is proposed to assess the uncertainty in damage localization, when the damage signatures fail to localize the damage uniquely. The uncertainty in damage quantification is evaluated through statistical non-linear regression, resulting in confidence bounds for the damage parameter. The uncertainties in damage detection, isolation and quantification are combined to quantify the overall uncertainty in diagnosis. The proposed methods are illustrated using two types of example problems, a structural frame and a hydraulic actuation system. Copyright © 2010 John Wiley & Sons, Ltd.
机译:本文在持续在线监测的背景下,开发了在损坏诊断(检测,定位和量化)中的三个步骤中的每一个中的每个步骤中的不确定性的方法。基于模型的方法用于诊断。不确定性的来源包括物理变异性,测量不确定性和模型错误。损坏检测基于标称和损坏的系统级响应之间的残差,使用统计假设测试,其不确定性可以容易地捕获。本地化基于源自系统模型的损坏签名的比较。提出了基于最小二乘法的度量来评估损坏定位的不确定性,当损坏签名无法唯一地造成损坏时。通过统计非线性回归评估损伤量化的不确定性,从而为损伤参数产生置信度。损伤检测,分离和量化的不确定性组合以量化诊断的总体不确定性。使用两种类型的示例性问题,结构框架和液压致动系统来示出所提出的方法。版权所有©2010 John Wiley&Sons,Ltd。

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