Detection of internal defects in as-built pipelines for structural health monitoring: A sensor fusion approach using infrared thermography and 3D Laser-scanned data

Abstract

Internal defects of pipelines are among the main factors causing accidents in the production phase of industrial plants. Periodic monitoring of a pipeline's inner surface condition is of great importance for minimizing the risk of failure of industrial plants. This study proposes a sensor fusion approach to detect internal defects automatically in as-built pipelines during their service lives to ensure structural safety. The proposed approach uses infrared thermography combined with three-dimensional (3D) laser-scanned data. For this purpose, a multi-sensor system equipped with a thermal infrared camera and a 3D laser scanner was internally and externally calibrated. From the combined data set, 3D points corresponding to the as-built pipelines are extracted from laser-scanned data. Then, thermographic analysis of the corresponding thermal data of those pipelines is performed. In this step, the local thermal gradients on the pipeline's surface are calculated to detect areas having different thermal values. In addition, the global thermal gradients along the longitudinal or radial axes of the pipeline are calculated to determine the consistency of its internal thickness. The field experiment was performed at an operating petrochemical plant to validate the proposed approach. The experimental results revealed that the proposed approach has potential for detecting internal defects in as-built pipelines from infrared thermography combined with 3D laser-scanned data.