Structural health monitoring in University of Western Australia-from research to application

Abstract

Structural Health Monitoring (SHM) has been attracting enormous research efforts around the world because it targets monitoring structural conditions to prevent catastrophic failure and to provide quantitative data for engineers and infrastructure owners to design reliable and economical asset management plans. With support from Australian Research Council (ARC), Cooperative Research Center for Integrated Engineering Asset Management (CIEAM) and Main Roads WA, intensive research works have been carried out in the School of Civil and Resource Engineering, the University of Western Australia (UWA), on various aspects of structural condition monitoring. These include sensor development, signal processing techniques, guided wave (GW) propagation methods, vibration-based methods, model-updating methods, and integrated local GW and global vibration-based methods. The performance of these techniques and methods are all affected by unavoidable noises and uncertainties in structural modeling and response measurements. Because uncertainties may significantly affect the reliability of SHM, research efforts have also been spent on modeling and quantifying some uncertainties associated with SHM. This chapter reports some of our research results related to Finite Element (FE) modeling errors, measurement noises and uncertainties associated with operation environments and signal processing techniques and reliabilities of different damage indices for SHM. Methods for modeling these uncertainties in SHM are also presented and discussed. The results presented in this chapter can be used to quantify possible uncertainties for a better SHM.