NSF Convergence Accelerator - Track D: Intelligent Surveillance Platform for Damage Detection and Localization of Civil Infrastructure

As a Co-PI of the convergence project, Dr. Qiang Cheng will be a subcontractor of the full NSF project awarded to Howard University, with his work mainly focusing on the following research activities: (a) Development of a prototype of a validated software module to extract displacements from a video that will automatically find and track key points from physical systems. For validation, the available experimentally measured displacements will be used to compare with the results that are extracted from the videos. (b) Development of a proof of concept of a calibrated ML-based damage detection and localization algorithm for a simple structure. The calibration will be based on the analysis of available data sets, simple laboratory experiments, and numerical simulations. He will be also helping other researchers, when necessary, with the development of other research activities of the proposed NSF project, including but not limited to the following: (c) Development of a prototype of a validated multi-resolution analysis module that logs responses of interest and processes video data to quantify damage features. This module extracts direct measures from the video point tracking such as displacement, deformation, and rotations. It also processes the video collected data to estimate variations of dynamic properties of the structures such as stiffness and damping. (d) Preliminary mapping for damage characterization and definition of features for uncertainty quantification for the selected benchmarks structural systems. (e) Selection of three benchmark structural systems to apply the proposed platform in Phase II. This selection will be made with the support of the industry advisory committee