Session: 04-01: Mechanics of Smart Structure Applications

Paper Number: 110685

110685 - Indoor Impact Event Localization via Velocity and Energy Ratio Mapping Function in Dispersive Media 

In this study, a new algorithm is proposed to improve impact event localization in vibration-based smart building applications. Impact event localization is an essential area of smart building research for applications such as occupancy estimation, patient monitoring, and intruder tracking. Currently, visual or audio sensors are often used for localization and tracking methods in smart buildings; however, these can be intrusive or unavailable in private areas such as restrooms. Vibration-based smart building systems, which use floor-mounted accelerometers, have the potential to be a less intrusive way to monitor building occupants. Vibration-based localization algorithms typically use a time or energy-based approach or a combination of the two. Time-based approaches generally rely on time-difference-of-arrival (TDOA) calculations and can have large errors due to the variability in the wave velocity caused by the dispersive properties of concrete, wave reflections from walls, and discontinuities in the floor structure such as beams under the floor. Energy-based localization methods have been shown to overcome the problem of variable wave velocity by using an exponential decay model of the generated wave energy to predict the location of an impact. Previous energy-based methods have been shown to give sub-meter accuracy for measurement systems with accelerometers mounted on the surface of the floor as well as systems with accelerometers mounted under the floor. However, available energy-based methods are limited to exponential decay models, which are only applicable to homogeneous floor structures. Supporting floor structures, such as beams, and walls create inhomogeneities, which causes the wave to decay differently in each direction and requires a more complex model to describe. This work proposes a new energy ratio mapping (ERM) algorithm to overcome this limitation. The ERM algorithm computes ratios of response energy between paris of sensors for impact locations across the floor structure to be monitored. The energy ratio maps act as a complex decay model of a mechanical wave in two dimensions and are used to predict the potential locations of an impact event. Experimental validation of the method is performed by collecting hammer impact data from 70 locations in a classroom within the Lab Science Commons Building at Tennessee Technological University from three under-floor-mounted sensors, and creating the energy ratio maps. Results of this study show that the ERM algorithm has the potential to be a highly accurate method for impact localization with at least one potential hit location falling within  of the correct location 97% of the time with an average of 3.5 potential hit locations for a given impact.

Presenting Author: Andrew Gothard Tennessee Technological University

Presenting Author Biography: Andrew Gothard is a second-year mechanical engineering Ph.D. student at Tennessee Technological University. His academic interests are centered around vibration-based smart building research. His research involves developing event localization, fall detection, and occupancy estimation algorithms using a combination of physics-based models and machine learning algorithms.