Damage Detection Accommodating Varying Environmental Conditions

Although many algorithms have been developed in the last two decades to detect damage in civil structures using dynamic properties, few studies have considered the challenge imposed by the variability of these properties due to changing environmental conditions. To address this concern, a statistically based analysis is proposed herein to analyze the distribution of identified structural parameters over an unknown number of external conditions and to effectively reduce their influence on the localization of damage. The proposed SHM scheme can be divided into three main steps: (1) identification of modal properties using acceleration responses of the structure to ambient loads under the influence of environmental conditions; (2) characterization of the structure as a function of the detected dynamic properties and an identification model (ID-model) representative of the system; and (3) accommodation of the influence of external conditions by means of a principal component analysis of the identified parameters. An analytical model of a four story, two-bay by two-bay building developed by the IASCM-ASCE Task Group on SHM benchmark problems is used to demonstrate the effectiveness of the proposed technique. The robustness of the technique is tested by considering modeling errors, as well as a considerable amount of sensor noise. Nine structural configurations are investigated with various temperatures and temperature gradients. The results indicate that the method is effective for detecting and locating damage.