Structural health monitoring with advanced nondestructive methods based on wavelet analysis

Steel structures, especially if they are exposed to the demanding loading or environmental conditions, need to be monitored concerning the actual in-service properties. For reliable monitoring it is important to know the initial properties in order to diagnose possible degradation with time. The target result of the presented research is to develop and apply the procedure for the degradation identification. The obtained results would serve as input for the model analysis that enables estimation of the structure condition and to support decision on the maintenance activities. In the experimental part of the presented research the model of the steel bridge was made to analyze the anomalous structural behavior and to optimize the selection of the appropriate monitoring methods. Various static and dynamic loads have been utilized on the model, with intentionally inserted steel structure failures (e.g. cracked bar, loosened screw joint). The structural responses are very well suited for the wavelet transforms and related wavelet analysis. This paper presents the procedure to correlate results of the wavelet analysis with the inflicted failures within the structure