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Advances in Non-Destructive Testing Methods for Weld Integrity Evaluation in High-Capacity Power Infrastructure

Solomon Atta, Prince Tofah, Oreoluwa Michael Adenuga

Abstract

Welded joints remain the most critical structural discontinuities in high-capacity power infrastructure, including boiler pressure parts, steam and gas turbine casings, penstocks, transmission tower assemblies, high-pressure piping, and wind turbine support structures. The integrity of these joints governs plant availability, personnel safety, and the economic life of capital assets that are increasingly required to operate under flexible, cyclic, and extended-life regimes. This paper reviews the state of the art in non-destructive testing methods for weld integrity evaluation as it stood at the beginning of the current decade, with emphasis on the transition from conventional single-element ultrasonic and film radiographic practice toward phased array ultrasonics, time-of-flight diffraction, full matrix capture with total focusing reconstruction, digital and computed radiography, advanced electromagnetic techniques, active thermography, acoustic emission monitoring, and robotic and data-driven inspection systems. The review synthesizes the physical principles, detection and sizing performance, codification status, and industrial deployment considerations of each family of methods, and examines the growing role of machine learning in automating defect recognition and classification. Application practice is surveyed across the principal welded asset classes of the power sector, from high-energy piping and boiler pressure parts to hydroelectric penstocks, wind turbine support structures, and transmission assets, and the qualification and reliability frameworks that govern industrial acceptance of new techniques are examined in detail. Persistent challenges are identified in the inspection of coarse-grained austenitic and dissimilar metal welds, in the detection of creep damage at its earliest stages, in the quantification of probability of detection for newly codified techniques, and in the management of large volumetric inspection datasets. The paper concludes that the convergence of array-based imaging, digital detectors, robotics, and learning algorithms is reshaping weld evaluation from a periodic pass-fail activity into a quantitative, data-rich input for structural integrity and remaining-life management of power assets.

Keywords

non-destructive testing; weld integrity; phased array ultrasonics; time-of-flight diffraction; digital radiography; acoustic emission; power infrastructure; machine learning www.iiardpub.org

References

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