RPA POSITIONING ERROR INFLUENCE ON CLOSE RANGE PHOTOGRAMMETRY FOR INDUSTRIAL INSPECTION

Abstract

In oil and gas offshore platforms, special pipelines as flexible risers make the connection between the ocean floor structures and the platform in extreme environmental and operational conditions. Periodic inspections are necessary to assess their integrity. As industrial climbing for inspection is expensive, extremely dangerous and time consuming, qualitative visual inspection with Remotely Piloted Aircraft System (RPAS), also known as drones, are being successfully applied for remote inspection of offshore flares and risers in a much safer, quicker, and cheaper way. These experiences motivate the 3D photogrammetric inspection of risers using RPAS, considering restrictions like layout of the inspected structures and surroundings and inability to prepare the scene. In this paper, taking advantage of the position information provided by the RPAS, the reconstruction and scale of the test scene were made using only GNSS data, GNSS and scale bars, RTK, and RTK and scale bars. Calibrated artifacts were used to evaluate the results and they include a PVC pipe with artificial defects simulating a riser, a pyramidal pattern with four spheres, and scale bars. The results showed that, as expected, the worst results are for GNSS data with error standard deviations of 0.35 mm compared with 0.20 mm or less for other options. For the sphere’s artifact, relative maximum sphere spacing errors are 9.3% for GNSS, 1.9% for RTK and 0.26% using scale bars. In any case it was possible to identify the defects in the pipe with good quality and with much more detail compared with a climbing inspection.