Researchers have developed an innovative algorithm and a compact FPGA-based system that can accurately locate defects in pipes using ultrasonic guided waves. This smart structural health monitoring (SHM) technology offers a cost-effective and scalable solution for real-time monitoring of pipeline integrity, a critical challenge faced by the oil and gas industry. By leveraging the unique properties of torsional ultrasonic waves, the system can pinpoint the location of defects such as cracks and mass loading on pipes, enabling early detection and prevention of potentially disastrous failures.
Tackling Pipeline Defects with Torsional Waves
Pipelines are the backbone of the oil and gas industry, transporting vast quantities of valuable resources across vast distances. However, these critical infrastructure assets face a constant threat from various forms of deterioration, including metal corrosion, mass loading, and structural defects. If left undetected, these issues can lead to catastrophic failures, causing environmental damage and substantial financial losses.
To address this challenge, researchers have explored the use of ultrasonic guided waves, a powerful non-destructive testing (NDT) technique that can traverse long distances along the pipe and detect early-stage defects. Among the different modes of guided waves, torsional waves have emerged as a particularly promising solution. These waves are non-dispersive, meaning they maintain their shape as they propagate, and are less affected by the presence of surrounding media, such as fluid inside the pipe or soil for buried pipes.
A Smart Solution for Pipe Inspection
In this groundbreaking research, a team of scientists from the Indian Institute of Technology Bombay has developed an innovative algorithm and a compact, FPGA-based (Field Programmable Gate Array) smart SHM system for on-board localization of defects in pipes using torsional ultrasonic guided waves.
The custom-designed FPGA board features a Xilinx Artix-7 FPGA and front-end electronics, enabling it to perform end-to-end SHM tasks, including:
– Actuating the PZT (lead zirconate titanate) thickness shear mode transducers to generate the torsional waves
– Acquiring and recording data from the PZT sensors
– Executing a novel damage localization algorithm to generate a damage index (DI) map that pinpoints the location of the defect on the pipe
Innovative Damage Localization Algorithm
The algorithm used in this system is a variation of the common source method, adapted for the cylindrical geometry of pipes. Unlike traditional techniques that require multiple transmission-reception cycles, this approach uses a common source to excite all the transmitter elements, and then records the signals on all receiver elements. This allows for efficient data acquisition and processing, making it well-suited for field deployment.
The algorithm works by metaphorically “unrolling” the pipe and visualizing it as a flat sheet, with the length representing the distance between the transmitter and receiver transducer rings, and the height representing the circumference of the pipe. It then generates a DI map, where each pixel value is computed based on the deviation of the received signal from the baseline (defect-free) condition.
Algorithm 1
Validated through Simulations and Experiments
The researchers have extensively validated the effectiveness of their smart SHM system through finite element (FE) simulations and experimental testing. The FE simulations demonstrated the algorithm’s ability to accurately localize both notch defects and mass loading (simulating external pressure) on the pipe, with localization errors typically less than 23 mm, a small fraction of the 400 mm separation between the transmitter and receiver transducers.
To further validate the system, the team conducted experiments using a steel pipe instrumented with shear mode PZT transducers and a custom-designed FPGA board. The results showed good agreement with the FE simulations, with the localization error from the experimental data analyzed on the FPGA being consistent with the results generated on a computer running Python code.
Unlocking the Full Potential of Guided Waves
The smart SHM system presented in this research overcomes several limitations of traditional NDT methods and laboratory-scale demonstrations, making it well-suited for field deployment in cost-sensitive scenarios. By integrating the data processing and damage assessment capabilities on the edge device, the system avoids the need for cloud connectivity and centralized data processing, which can be challenging in remote pipeline locations.
Furthermore, the system’s low power consumption (approximately 0.3 watts) and compact form factor make it scalable for managing data from hundreds or thousands of deployments, a crucial requirement for the increasing automation in pipeline management. The researchers believe that this technology has the potential to unlock the full potential of guided wave-based SHM, enabling real-time monitoring and early detection of defects in pipelines, ultimately enhancing the safety and reliability of critical infrastructure.
Author credit: This article is based on research by Sheetal Patil, Sauvik Banerjee, Siddharth Tallur.
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