Recent research had shown that displacements of bridges under traffic can capture critical changes in bridge serviceability and safety. Measuring bridge movement under trains in the field is difficult and expensive because a fixed reference point is not normally available, thus creating the need to erect independent scaffolding to create good reference points near the bridge from where to measure.
The goal of this research is to develop, investigate, and test UAV and laser system technology that can measure reference-free, non-contact dynamic displacements to inform railroad owners towards bridge management prioritization and safety. The research method approach consisted of (1) software development in laboratory settings to collect displacement data from a moving laser, (2) hardware selection and integration that is compatible with railroad environments, (3) laboratory test and validation of the new system in comparison with traditional sensing system, and (4) field validation in outdoor settings test and validation.
The proposed technology reduces the efforts, risk, time, and cost involved in acquiring transverse displacements under loading operations and can be implemented for efficient infrastructure monitoring across various industries. The results obtained from this research showed that the integration of UAS and laser systems can effectively collect data related to the dynamic performance of railroad bridges across the network. The same system can be used to collect dynamic displacements of other infrastructure components of the railroad system safely and accurately. The next steps of this research include the testing of the system in the field in collaboration with railroad bridge owners, so the technology can be validated under revenue service traffic.
