A Method to Detect Structural Damage Using High-Frequency Seismograms

There has been recent interest in using acoustic techniques to detect damage in instrumented civil structures. An automated damage detection method that analyzes recorded data has application to building types that are susceptible to a signature type of failure, where locations of potential structural damage are known a priori. In particular, this method has application to the detection of brittle fractures in welded beam-column connections in steel moment-resisting frames (MRFs). Such a method would be valuable if it could be used to detect types of damage that are otherwise difficult and costly to identify. The method makes use of a prerecorded catalog of Green's function templates and a matched filter method to detect the occurrence and location of structural damage in an instrumented building. This technique is different from existing acoustic methods because it is designed to recognize and use seismic waves radiated by the original brittle failure event where the event is not known to have occurred with certainty and the resulting damage may not be visible. The method is outlined as follows. First, identify probable locations of failure in an undamaged building. In pre-Northridge steel MRFs, which are susceptible to brittle failure of welded beam-column connections, those connections would be the locations of probable failure for this type of building. Second, obtain a Green's function template for each identified location of probable failure by applying a short-duration high-frequency pulse (e.g. using a force transducer hammer) at that location. One underlying assumption of this method is that the Green's function template specific to a potential location of failure can be used to approximate the dynamic response of the structure to structural damage at that location. Lastly, after a seismic event, systematically screen the recorded high-frequency seismograms for the presence of waveform similarities to each of the catalogued Green's function templates in order to detect structural damage. This is achieved by performing a running cross-correlation between each Green's function template and a moving window of the continuous data recorded during the earthquake. Damage that occurs at one of the catalogued potential locations is expected to result in a high cross-correlation value when using the correct Green's function template. This method, also known as the matched filter method, has seen recent success in other fields, but has yet to be explored in the context of acoustic damage detection in civil structures. Preliminary experimental results from tap tests performed on a small-scale laboratory frame are presented. Cross-correlation calculations highlight similarities among events generated at the same source location and expose differences among events generated at different source locations. Finally, a blind tap test is performed to test whether cross-correlation techniques and catalogued Green's function templates can be used to identify the occurrence of and pinpoint the location of an assumed-unknown event.