Bridges, Tunnels and other Transportation Structures
The use of laser scanning in the realm of bridge assessment has been primarily limited to measuring clearances and bridge dimensions such as span length, deck width, and girder spacing. Given the scale of these measurements compared to standard accuracy metrics for typical LiDAR sensors, it follows that they may be captured with relatively small errors (< 1%). The objective of this paper is to explore the capability of LiDAR to (a) estimate smaller dimensions such as flange thickness, flange width, and girder depth, and (b) quantify the observed errors in terms of their influence on capacity calculations (as opposed to simple percent errors). To satisfy these objectives, an eleven-span steel girder bridge carrying the I-76 highway in Bala Cynwyd, PA was subjected to a total of sixteen LiDAR scans under normal operating conditions. Various dimensional quantities were then extracted from the data both directly and using standard plane-fitting approaches. Results indicated that dimensions obtained from plane fitting resulted in flexural capacities between 4% and 7% less than those computed using the dimensions from the bridge plans. In contrast, the dimensions obtained directly from the point cloud data resulted in capacity errors of approximately 16%. In addition, during a detailed examination of the point cloud data, ripple patterns were found randomly along horizontal elements, such as the bottom flanges of girders. These patterns were examined and traced to the vibration of the bridge caused by heavy truck traffic that occurred periodically during the data collection period. This finding was confirmed through the simulation of a vibrating plate, which had the same amplitude and frequency of the I-76 bridge. The ability of LiDAR sensors to accurately characterize such responses opens up new opportunities for their use as a means to capture structural responses as well as geometric information. In addition, if not properly identified as anomalies resulting from operational vibrations, such ripple patterns may increase errors associated with static dimensions and may lead to erroneous diagnoses.