Date Approved
6-7-2023
Embargo Period
6-13-2023
Document Type
Thesis
Degree Name
Master of Science in Civil Engineering
Department
Civil and Environmental Engineering
College
Henry M. Rowan College of Engineering
Advisor
Adriana Trias, Ph.D.
Committee Member 1
Islam Mantawy, Ph.D.
Committee Member 2
Andres Roda, PE
Keywords
LIDAR, bridge inspection, bridge decks
Subject(s)
Bridges--Maintenance and repair; Bridges--New Jersey; Nondestructive testing
Disciplines
Civil and Environmental Engineering | Engineering
Abstract
Bridge deck condition assessments are typically conducted through visual physical inspections, utilizing traditional contact sensors for Non-Destructive Evaluation techniques such as hammer Sounding and chain dragging which require the expertise of trained inspectors. However, the accuracy of these inspections is limited by the level of deterioration of the bridge deck, as the ability of the inspectors is proportional to the apparent level of damage. This study aims to improve the accuracy of bridge deck inspection processes by utilizing non-destructive evaluation techniques, including the analysis of point cloud data gathered via Light Detection and Ranging (LiDAR) as a geometry-capturing tool. The overall goal of this research is to evaluate and quantify the effectiveness and efficiency of LiDAR sensors in contributing to the suite of technologies available to perform bridge deck condition assessment. To achieve this, the research proposes to understand the deterioration pattern of New Jersey bridges, evaluate the results gathered from point cloud data collected on a full-scale bridge deck, quantify the information gained from deploying LiDAR on operating bridges in New Jersey, and investigate the costs related to current bridge condition assessment practices and the impact of incorporating the use of LiDAR sensors. Two data processing approaches were chosen to measure gross and fine dimensions of the evaluated bridge decks, resulting in an accuracy of 96% with respect to results gathered from inspection reports.
Recommended Citation
Al Shaini, Issa Nidal, "THE USE OF POINT CLOUD DATA TO SUPPORT CONCRETE BRIDGE DECK CONDITION ASSESSMENT" (2023). Theses and Dissertations. 3131.
https://rdw.rowan.edu/etd/3131