Development of an algorithm to measure defect geometry using a 3D laser scanner

Abstract

Current fatigue life prediction models for coiled tubing (CT) require accurate measurements of the defect geometry. Three-dimensional (3D) laser imaging has shown promise toward becoming a nondestructive, non-contacting method of surface defect characterization. Laser imaging provides a detailed photographic image of a flaw, in addition to a detailed 3D surface map from which its critical dimensions can be measured. This paper describes algorithms to determine defect characteristics, specifically depth, width, length and projected cross-sectional area. Curve-fitting methods were compared and implicit algebraic fits have higher probability of convergence compared to explicit geometric fits. Among the algebraic fits, the Taubin circle fit has the least error. The algorithm was able to extract the dimensions of the flaw geometry from the scanned data of CT to within a tolerance of about 0.127 mm, close to the tolerance specified for the laser scanner itself, compared to measurements made using traveling microscopes. The algorithm computes the projected surface area of the flaw, which could previously only be estimated from the dimension measurements and the assumptions made about cutter shape. Although shadows compromised the accuracy of the shape characterization, especially for deep and narrow flaws, the results indicate that the algorithm with laser scanner can be used for non-destructive evaluation of CT in the oil field industry. Further work is needed to improve accuracy, to eliminate shadow effects and to reduce radial deviation.