Experimental studies on multi‐scale data‐driven methods within the framework of structural health monitoring

Abstract The German Research Foundation has established the priority program SPP 100+. Its subject is monitoring bridge structures in civil engineering. The data‐driven methods cluster deals with the use of measurements and their special global and local analysis methods, which complement each other in an overall multi‐scale concept in order to realize condition monitoring. The presented methods aim for damage detection, localization, and quantification of the monitored structure. Static and dynamic investigations based on mechanical multi‐scale models were carried out, and process‐oriented models combined with image processing methods and machine learning were created. The methods are tested on several laboratory and real‐life experimental mechanical structures. The underlying theoretical concept and first experimental results of the research group are presented in this article. This study successfully employs a series of multi‐scale experiments, integrating mechanical models and advanced image processing to effectively detect, localize, and quantify damage in bridge structures for enhanced structural health monitoring.