Uncertainty quantification in structural damage diagnosis

作者：Sankararaman Shankar; Mahadevan Sankaran^*

来源：Structural Control and Health Monitoring, 2011, 18(8): 807-824.

DOI：10.1002/stc.400

• structural health monitoring
• damage diagnosis
• damage detection
• confidence intervals
• uncertainty quantification
• bond graph
• non-linear regression
• F-statistic
• inverse problems

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.

• 出版日期2011-12