ABSTRACT
Structural Health Monitoring (SHM) systems are comprised of a grid of sensors installed at a fixed location on structures to detect the presence of defect, localize the detected defect, quantify its severity, and estimate the Remaining Useful Life (RUL). SHM system performance is currently assessed based on Probability of Detection (POD) of defects, which is a function of defect size. This performance parameter was inherited from Non-Destructive Testing (NDT), where a human operator performs inspection on a structure at a given location, with mobile sensors. For SHM systems, POD and Probability-of-False-Alarm (PFA) are a measure for only detection of defects. Furthermore, these parameters could vary over time as sensors degrade. This paper presents a methodology to characterize the performance of SHM systems with respect to damage detection, localization, and assessment. Probability theorem is used to characterize uncertainties associated with the SHM process, and Bayes theorem is employed to determine its reliability. The methodology is then tested on vibration-based modal strain energy SHM technique applied to a numerical Finite Element Analysis (FEA) study conducted on an offshore energy structure.
