Structural Health Monitoring of Steel Girder Bridge Using Photogrammetry and LiDAR Scan Technology: Proof of Concept

Abstract

Bridges require regular inspection and maintenance; however, traditional inspections are performed manually at prescribed intervals, involving substantial manpower, high costs, and safety risks due to the challenging locations of many bridges. To address these limitations, the present study focused on developing a methodology to automate technical inspections of bridges using a hybrid approach combining LiDAR and photogrammetry. Unlike past drone inspections, which were largely limited to basic photography and videography, this approach integrates advanced technologies for more comprehensive data collection. For this purpose, a single-span steel girder bridge with a span of 45.7 meters, located between Beas and tto Tanda in the state of Punjab, India, was selected. A Proof-of-Concept (PoC) was developed using high-fidelity digital models, created through photogrammetry with UAV-mounted high-resolution cameras and LiDAR, to carry out 16 inspection missions. The development of these high-fidelity digital models enabled flexible viewing, analysis, and measurement of various structural parameters, including the schedule of dimensions diagram, camber, distortions, rail levels, creep, and eccentricity. The parameters measured from the digital models were compared with the limiting values specified by RDSO, as well as with manually collected data. It was observed that the dimensional measurements obtained through the automated technology were within ±5 mm of the drawings and previous inspection reports, indicating that photogrammetry combined with LiDAR is a reliable and effective alternative technology for bridge inspection