Pipeline health monitoring using helical guided ultrasonic waves

Pipelines are a vital component in the gathering, transmission, and distribution networks of oil and gas products around the globe. Monitoring the structural integrity of pipes is extremely important because it enables normal operational conditions, minimizes fatal accidents, and eliminates environmental destruction. Many pipeline accidents are reported each year in the US with corrosion being one of the most common forms of failure causing significant wall-thickness and pressure loss. To this aim, this thesis investigates the use of active and passive acoustic methods to localize, monitor, and quantify corrosion in steel pipelines. This is achieved by exploiting the helical guided ultrasonic waves (HGUW) in combination with numerical modeling and advanced data processing techniques. The main advantage of using the HGUW over traditional guided waves is the ability to use a small number of permanently attached sensing units, shifting the paradigm towards an automated and autonomous pipe health monitoring scheme. As far as active monitoring is concerned, a two-step corrosion localization and quantification algorithm has been developed using the HGUW. This algorithm combines a well-establish medical imaging algorithm, the algebraic reconstruction technique (ART), along with 2-dimensional acoustic modeling to detect and reconstruct different defects. This method relies on the scattering of the incident guided waves on surface anomalies. To establish the sensitivity of the guided modes to different corrosion profiles, finite element simulations were carried out using ABAQUS commercial software. Several experiments have been conducted to evaluate the performance of the algorithm including an accelerated corrosion test with the findings suggesting that a 5-ft long, 12-in diameter pipe can be effectively screened for high contrast defects using only six sensors. Furthermore, the potential of using the acoustic emission (AE) technique to passively monitor corrosion was also investigated. This was achieved by collecting HGUW-type AE activity produced by corrosion mechanisms like pitting and surface peeling. The use of the b-value analysis was proposed for processing the AE activity which could reveal the corrosion intensity as well as indicate critical states of the corrosion evolution in the pipe. This method was validated using an accelerated corrosion experiment as well as finite element simulations. Overall, a good correlation was observed between theoretical, experimental, and numerical results suggesting that the HGUW can be utilized in both active and passive modes to assess the structural condition of pipelines.