Experimental evaluation of environmental effects on a polymer-coated aluminium structure: a time-series analysis and pattern recognition approach

摘要

Temperature variation is an important issue that needs to be considered when trying to develop a reliableudStructural Health Monitoring (SHM) strategy. In the case that a data-based approach is chosen for damageuddetection, environmental fluctuations could be erroneously regarded as an abnormal condition of theudstructure and could mask the presence of damage. One of the objectives of the current work is to examineuda statistical pattern recognition approach for novelty detection under different temperature conditions. Audsecond important issue that could hinder the reliability of a SHM strategy is any kind of nonlinearudbehaviour, not associated with damage, in a system. For the purposes of this paper, the dynamic behaviourudof a polymer-coated aluminium structure with ribs fixed with bolts is examined. The autoregressiveudparameters are the damage sensitive features and later, it is performed Principal Component Analysisud(PCA) for robust novelty detection that takes into account the temperature variation.