Characterizing human activity induced impulse and slip-pulse excitations through structural vibration

Abstract

Many human activities induce excitations on ambient structures with various objects, causing the structures to vibrate. Accurate vibration excitation source detection and characterization enable human activity information inference, hence allowing human activity monitoring for various smart building applications. By utilizing structural vibrations, we can achieve sparse and non-intrusive sensing, unlike pressure- and vision-based methods. Many approaches have been presented on vibration-based source characterization, and they often either focus on one excitation type or have limited performance due to the dispersion and attenuation effects of the structures. In this paper, we present our method to characterize two main types of excitations induced by human activities (impulse and slip-pulse) on multiple structures. By understanding the physical properties of waves and their propagation, the system can achieve accurate excitation tracking on different structures without large-scale labeled training data. Specifically, our algorithm takes properties of surface waves generated by impulse and of body waves generated by slip-pulse into account to handle the dispersion and attenuation effects when different types of excitations happen on various structures. We then evaluate the algorithm through multiple scenarios. Our method achieves up to a six times improvement in impulse localization accuracy and a three times improvement in slip-pulse trajectory length estimation compared to existing methods that do not take wave properties into account.