Deformation Monitoring Using UAS and Photogrammetry – Seminoe Dam

Submitted by atripp on

Dam safety is an ongoing concern for the BOR. In the interests of maintaining modern dam safety monitoring, BOR has started to investigate the use of small unmanned aircraft systems (sUAS) to improve safety, reduce costs, and increase effectiveness. The Seminoe Dam in Wyoming is currently being used as a test subject.  Alkali Silica Reaction (ASR) has been causing dimensional changes at Seminoe Dam for many years. These changes eventually form cracks throughout the structure. Given the immensity of the structure, monitoring the dimensional changes are time-consuming and difficult to obtain. The use of UAS-derived imagery has the potential to provide BOR engineers and managers with high-resolution, high-accuracy data to detect cracks and changes, and make important decisions regarding the safety of the dam with confidence. If successful, photogrammetric solutions can provide a low-cost alternative to measuring and monitoring dam movement and degradation.
 

This project looks at two types of movement: 1) movement due to loading and 2) movement due to ASR. The movements will be detected using a photogrammetry method that triangulates the position of each pixel from a collection of overlapping images taken by a digital camera to develop a 3D point cloud. The 3D point cloud can be exported into most of the popular CAD formats for further analysis. It is expected that the image resolution for crack detection will be between 1/8 and 1/4 inch. The geometric model resolution for difference modeling will be between 0.3 and 0.5 of the image resolution (between 0.0375 and 0.125 inch). At this point, the offset between the camera and the subject determines the final resolution. Due to limitations on the UAS and camera, a maximum offset of between 30 and 40 feet will be maintained. If additional equipment becomes available, this may be used to increase the resolution if necessary.
 

3D model generated from sUAS photography and photogrammetric software.

Sensor
Platform
Author Name
David Salas; Matthew Klein
Author Email
desalas@usbr.gov; mjklein@usbr.gov