A helical-based ultrasonic imaging algorithm for structural health monitoring of large-diameter metallic pipelines
Stylianos Livadiotis a*, Arvin Ebrahimkhanlou b, Salvatore Salamone c
Smart Structures Research Group (SSRG), Department of Civil, Architectural and Environmental Engineering-University of Texas at Austin
a firstname.lastname@example.org, b email@example.com , c firstname.lastname@example.org
The pipeline network around the U.S. is aging, and corrosion has been the predominant cause of failure. Conventionally, the assessment of pipelines relies on periodic visual inspections, which are time-consuming, costly, and depends heavily on the skills of the inspectors. Several nondestructive techniques have been developed in recent years; however, there still exists the need to shift towards a continuous health monitoring scheme achieved through a low-cost permanently installed system. This work aims at combining guided ultrasonic waves and advance tomographic algorithm to locate corrosion-induced defects in the inner and outer surface of large-diameter steel pipes. Particularly, it employs guided ultrasonic waves that propagate on helical paths around pipes. The novelty of this work is in using high orders of the so-called helical guided ultrasonic waves (HGUW), which can significantly increase the inspection area with a minimal number of sensors. Such waves could be excited and sensed with low-cost piezoelectric disks. Algebraic reconstruction algorithm (ART) is then implemented in order to gather information from the wave propagation through the pipe and asses possible locations where defects might exist. To validate the proposed imaging algorithm, numerical simulation and experiments were carried out. For the numerical simulation, a finite element model was used to simulate wave propagation in a 12in-diameter steel pipe. The numerical model simulates damage by reducing the thickness of the pipe in selected locations. In addition, experiments were performed on a pipe with the same size, and damage was simulated using a pair of magnets. Both final defect estimation images from the numerical simulations and the experiment accurately localized the damage. These results suggest that the proposed imaging algorithm can be effectively used for continuous monitoring of corrosion damage in pipelines.
Keywords: Structural Health Monitoring, Pipelines, Guided Ultrasonic Waves, Imaging Algorithm, Finite Element Modeling, Damage Localization