An Approach to Bridge Inspection Using 3D Laser Scanners and Digital Photographs

Abstract

Bridges are an integral component of infrastructure systems, which play a critical role in the development of the economy, society, and national security. However, bridges have not received adequate care and are deteriorating rapidly. More than 9% of bridges in the United States are structurally deficient and need immediate repairs. A major contributing factor to this deficiency is a lack of adequate and accurate inspection processes. Current methods of bridge inspection and assessment involve a reiterative paper-based process that requires manual data entry and extraction. The inspection team analyzes the critical portions of a bridge, identifies problem severity, documents the damages and concentrates on the cause of the problem. This paper-based process is complex, time-consuming and error-prone. To eliminate human errors attached with surveying and the data collection process, practitioners recently have used automated techniques and advanced equipment to inspect bridge conditions. This research introduces a combination of 3D laser scanning and photographic techniques to determine important attributes of bridge inspection. A terrestrial laser scanner is used to collect point cloud data to create a 3D model of the bridge structure. Three-dimensional geometrical information of bridge structure is extracted from the point cloud 3D model with accuracy level in accordance with national bridge inventory (NBI) specifications. The occurrence of cracks in bridge components is a clear sign of potential damage and must be assessed critically. In order to determine the severity of damage, it is important to compute the width of cracks and compare the data with an allowable limit as specified by NBI or state department of transportation (DOT). In addition, to examine geometrical surveying data, this research proposes a framework to detect cracks in the bridge structure. The framework is verified and validated using a case project. The results of this study contribute to the construction engineering and management body of knowledge by demonstrating the extraction of geometric data for bridge inspection in accordance with NBI accuracy specifications using a laser scanner. This study also demonstrates an automated technique to assess structural health by detecting cracks in a concrete bridge using digital photographs and computing the width of those cracks.