Edd Hauser

Small-Format Aerial Photography for Highway-Bridge Monitoring

Small-format aerial photography (SFAP) is a low-cost solution for bridge-surface imaging and is proposed as a remote bridge-inspection technique to supplement current bridge visual inspection. Providing top-down views, photos taken from airplanes flying at 305 m (1,000 ft) allow for the visualization of subinch (i.e., large) cracks and joint openings on bridge decks or highway pavements. An onboard global positioning system can help geo-reference images collected and allow automated damage detection. However, the site lighting, surrounding tree shades, and highway surface reflectivity may affect the quality of the images. Several examples of bridge evaluation using SFAP are presented to demonstrate the capability of remote sensing as an effective tool for bridge-construction monitoring and condition assessment. A deck condition rating technique for large crack detection is proposed to quantify the condition of the existing bridge decks.

LiDAR Scan for Blasting Impact Evaluation on a Culvert Structure

This paper summarizes a case study of using three-dimensional (3D) light detection and ranging (LiDAR) scanner technology in bridge postblast geometric assessments. Terrestrial 3D LiDAR scanners can generate dense point clouds of position information that can be used to establish baseline geometric information for structures and to establish critical dimensional footprints for before and after event comparisons. For close range blast effects, the preblast and postblast scans of a bridge are proposed to establish blasting induced effects and damage information. The Colony Road culvert bridge was monitored for a nearby construction blasting, where full-scale 3D scans of the bridge have been conducted before and after blasting. The critical sections and geometries are then compared to ensure the safety of the bridge.

Three-Dimensional Terrestrial LIDAR for Operational Bridge Clearance Measurements

AbstractThis paper reports the outcomes of a study of the vehicle crossing effects on a terrestrial light detection and ranging (LIDAR) scan on highway bridges for underclearance measurements. Ground-based or vehicle-mount terrestrial LIDAR scanners, which recreate the bridge structure as a three-dimensional point cloud of thousands of position data points, have been found to be ideal for bridge clearance measurements. To determine the effects of ambient overhead vehicle crossing and seasonal temperature variation on clearance measurements, periodic monitoring of the Harris Road Bridge has been conducted. A simplistic but practical correlation analysis is performed, which shows that operational LIDAR scanning is a viable technique for bridge clearance measurements.

3D terrestrial lidar for operational bridge clearance measurements

This paper reports the outcomes of a study of the vehicle crossing effects on terrestrial LiDAR scan on highway bridges for underclearance measurements. Ground-based or vehicle-mount terrestrial LiDAR scanners, which recreate the bridge structure as 3D point cloud of thousands of position data points, have been found to be ideal for bridge clearance measurements. To determine the effects of ambient overhead vehicle crossing and seasonal temperature variation on clearance measurements, periodic monitoring of the Harris Road Bridge has been conducted. A simplistic but practical correlation analysis is performed which shows that operational LiDAR scanning is a viable technique for bridge clearance measurements.

The role of terrestrial 3D LiDAR scan in bridge health monitoring

This paper addresses the potential applications of terrestrial 3D LiDAR scanning technologies for bridge monitoring. High resolution ground-based optical-photonic images from LiDAR scans can provide detailed geometric information about a bridge. Applications of simple algorithms can retrieve damage information from the geometric point cloud data, which can be correlated to possible damage quantification including concrete mass loss due to vehicle collisions, large permanent steel deformations, and surface erosions. However, any proposed damage detection technologies should provide information that is relevant and useful to bridge managers for their decision making process. This paper summaries bridge issues that can be detected from the 3D LiDAR technologies, establishes the general approach in using 3D point clouds for damage evaluation and suggests possible bridge state ratings that can be used as supplements to existing bridge management systems (BMS).

Remote sensing for bridge health monitoring

This paper addresses the potential applications of commercial remote sensing (CRS) technologies for bridge monitoring. High resolution optical-photonic images can provide bridge damage information including through-deck collision damages, large permanent deformations, overload cracking and surface erosions, as well as surrounding environmental information. This paper summaries bridge issues that can be detected from high resolution remote sensing imageries based on visual interpretation as guidance for remote sensing imagery based bridge inspection, and the development of future automatic detection methods. A LiDAR based automatic bridge evaluation system LiBE (LiDAR Bridge Evaluation) is introduced in this paper with an application example of a test bridge maintained by the Los Angeles County (CA) Department of Public Works. Laser scanning techniques have also been used for bridge load testing in a new bridge near Charlotte, NC and maintained by the North Carolina DOT. The primary results of these preliminary tests are also presented. Remote sensing techniques are introduced as a supplement to the existing, required visual bridge inspections.

Small-format fly-over photography for highway bridge monitoring

Current bridge visual inspections are time-consuming, subjective, and rely heavily on personal experiences. The resulting ratings may be inconsistent. This paper discusses using remote-sensing technologies for bridge assessment, specifically, the use of high-resolution aerial imagery. The Small-Format Aerial Photography (SFAP) is a low-cost solution for bridge surface imaging. Providing top-down views, the airplanes flying at 1000 ft, can allow visualization of sub-inch (< 0.5 inch) cracks and joint openings on bridge decks or highway pavements. However, the site lighting may influence the quality of the images; surrounding tree shades and the highway wear surface reflectivity. Several examples of bridge evaluation using SFAP aerial photography are presented to demonstrate the capability of remote sensing as an effective tool for bridge construction monitoring and condition assessment. Several imaging issues are raised about analytical techniques that are necessary to ensure proper quantification of bridge problems, which include crack detection, movement determination, heavy trucking assessment, debris detection, channel width determination and environment assessment.

Bridge deck joints evaluation using lidar and aerial photography

Deck joint is important for a bridge - Any cost-effective evaluation methods that can help trace joint movements during frequent inspections will provide valuable data to bridge engineers. In this paper, 3D Terrestrial LiDAR and Aerial photography are being investigated as possible joint evaluation methods. The laser scanners record 3D positions of the surface points, generating high density point clouds. Aerial images taken by commercial DSLR cameras in a small airplane flying at 1000 feet, generates high resolution imagery. Both techniques have sub-inch pixel resolutions. Scanning results from bridges in both Florida and Alabama have shown that LiDAR and aerial imaging technologies are compatible techniques and can be applied in bridge deck joint performance evaluation. Moreover, both techniques have the potential to reduce the costs in bridge inspection.

Development of a baseline model for a steel girder bridge using remote sensing and load tests

A new skewed two span continuous steel girder bridge was constructed and opened to traffic recently. This bridge uses high performance steel (HPS 100W) in the flanges of the negative moment region over the intermediate pier. For construction verification and long-term structural health monitoring purposes, a finite element (FE) model was developed for the bridge superstructure. Various field tests were performed to verify the model: 1) LiDAR scan, 2) static truck load tests, and 3) Laser doppler vibrometer testing. LiDAR scanner was introduced to gain geometrical information of the bridge in the real world. It was also used to measure girder deflections during load tests. The fundamental frequency of the bridge vibration was obtained by using a Laser doppler vibrometer. Both dynamic and static measurements are then used to update the FE model. This valid bridge superstructure FE model was provided to local DOT bridge engineers with the completion of this study.

Remote Sensing for Bridge Monitoring

Commercial remote sensing (CRS) as robust bridge health monitoring techniques offer unique features that are missing from current embedded structural health monitoring systems, including the ability to geo-reference bridge location, provide spatial views and high-resolution top views of bridges. Beginning in 2007, a research partnership (University of North Carolina at Charlotte, ImageCat Incorporated, Boyle Consulting, Charlotte Department of Transportation and North Carolina Department of Transportation) has completed a proof-of-concept project to develop ground-based LiDAR scan and sub-inch-resolution aerial photography into the IRSV (Integrated Remote Sensing and Visualization) bridge data diagnostic system. The IRSV system represents a critical juncture towards “Total View Total Integration (TVTI)” infrastructure monitoring concept and provides further incentive for CRS development. This paper presents a high-level discussion on the potentials of CRS tools to enhance bridge inspection and data management.