Tunnel structural condition inspections and asset component reporting have traditionally been conducted manually. This process can be expensive, time-consuming and with inconsistent data capture leading to challenges in cross-referencing vital condition information spatially and tracking condition over time.
Being long, linear assets, tunnel condition reporting relies on assessing changes in asset condition and previous metrics. However, there are constraints such as safety risks, tunnel closure time frames, and the costs of working on heights and in confined spaces.
This project set a new benchmark in engineering technologies by combining LiDAR scanning technology, high-resolution cameras, and photogrammetric processing to derive a geometrical and visual depiction of the tunnel. This high-fidelity dataset formed the ‘digital twin’ base layer, used to identify defects and features (cracks, cables, etc.) at a relative location accuracy of 10 mm and image resolution of 1 mm x 1 mm. The tunnel scanner system provided a complete geometrical and visual depiction of the recorded tunnel surface at a specific time. Recordings captured by the tunnel scanner were high-quality as-built documentation, and the efficient software allowed in-depth and versatile data evaluations and engineering judgements to be made.
This new and innovative process, deployed in Australia for the first time; enabled AECOM and Intellispatial to provide real-time data and quality reporting to Transurban Queensland. This data capture can be used to compare changes over time and support better decision-making in the future, making inspections more efficient, safer, and easier.
