Uncertainty quantification in structural health monitoring

Abstract

Structural health monitoring (SHM) involves detection, isolation and quantification of damage in engineering systems. This paper focuses on methods for the quantification of uncertainty in each of these procedures, in the context of continuous online monitoring. Sources of uncertainty include, but are not limited to, physical variability, measurement uncertainty and model uncertainty. Damage detection is based on statistical hypothesis testing whose uncertainty can be captured easily. Isolation is based on the comparison of fault signatures and sometimes the observed signatures may not uniquely isolate faults, thus causing uncertainty in fault isolation. A metric based on least squares is proposed to assess the confidence in fault isolation, when the fault signatures fail to isolate faults uniquely. The uncertainty in damage quantification is evaluated through statistical non-linear regression and confidence limits for the damage parameter are calculated. The procedures are then illustrated using two types of example problems, a structural frame and a hydraulic actuation system. Copyright © 2009 by the American Institute of Aeronautics and Astronautics, Inc.