Ultrasonic testing in the field of engineering joining

Fan, Zongkai; Bai, Keran; Chen, Chao

doi:10.1007/s00170-024-13569-w

Cited by 3 publications

(1 citation statement)

References 103 publications

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“…Damage detection in steel pipes is an essential challenge for non-destructive testing (NDT). Different NDT techniques have been employed for damage monitoring on ferromagnetic pipes, including liquid penetrant tests [4], ultrasonic tests [5], dynamic permeability testing [6], corrosion monitoring techniques [7], visual inspection and assessment techniques [8], eddy current testing [9], magnetic flux leakage testing [10], and X-ray inspection [11]. Defects in ferromagnetic pipes can be detected using liquid-penetrant testing based on the accumulation of a liquid around the defect on the sample surface.…”

Section: Introductionmentioning

confidence: 99%

Inspection of Semi-Elliptical Defects in a Steel Pipe Using the Metal Magnetic Memory Method

Villegas-Saucillo,

Diaz-Carmona,

Prado-Olivares

et al. 2024

Applied Sciences

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Ferromagnetic pipes are widely used for fluid transportation in various industries. The failure of these ferromagnetic pipes due to surface defects can generate industrial accidents, economic losses, and environmental pollution. Non-destructive testing techniques are required to detect these surface defects. An alternative is the metal magnetic memory (MMM) method, which can be employed to detect surface flaws in ferromagnetic structures. Based on this method, we present an analysis of experimental results of the magnetic field variations around five different surface semi-elliptical defects of an ASTM A36 steel pipe. A measurement system of MMM signals is implemented with a rotatory mechanism, a magnetoresistive sensor, a data processing unit, and a control digital unit. The MMM method does not require expensive equipment or special treatment of the ferromagnetic structures. In order to research a potential relationship between the defect sample size and the measured MMM signals, variable defect dimensions are experimentally considered. According to these results, the shape and magnitude of the normal and tangential MMM signals are altered by the superficial semi-elliptical defects. In particular, the maximum and mean tangential components and the maximum and minimum normal components are related to the defect dimensions. The proposed measurement system can be used to study the behavior of magnetic field variations around surface defects of ferromagnetic pipes. This system can be adapted to measure the position and damage level of small defects on the surface of ferromagnetic pipes.

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Section: Introductionmentioning

confidence: 99%

Inspection of Semi-Elliptical Defects in a Steel Pipe Using the Metal Magnetic Memory Method

Villegas-Saucillo,

Diaz-Carmona,

Prado-Olivares

et al. 2024

Applied Sciences

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Crack Detection Method for Wind Turbine Tower Bolts Using Ultrasonic Spiral Phased Array

Sun,

Dong,

Diao

et al. 2024

Sensors

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High-strength bolts are crucial load-bearing components of wind turbine towers. They are highly susceptible to fatigue cracks over long-term service and require timely detection. However, due to the structural complexity and hidden nature of the cracks in wind turbine tower bolts, the small size of the cracks, and their variable propagation directions, detection signals carrying crack information are often drowned out by dense thread signals. Existing non-destructive testing methods are unable to quickly and accurately characterize small cracks at the thread roots. Therefore, we propose an ultrasonic phased array element arrangement method based on the Fermat spiral array. This method can greatly increase the fill rate of the phased array with small element spacing while reducing the effects of grating and sidelobes, thereby achieving high-energy excitation and accurate imaging with the ultrasonic phased array. This has significant theoretical and engineering application value for ensuring the safe and reliable service of key wind turbine components and for promoting the technological development of the wind power industry.

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Application of Object Detection Algorithms in Non-Destructive Testing of Pressure Equipment: A Review

Wang,

Chen,

Han

et al. 2024

Sensors

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Non-destructive testing (NDT) techniques play a crucial role in industrial production, aerospace, healthcare, and the inspection of special equipment, serving as an indispensable part of assessing the safety condition of pressure equipment. Among these, the analysis of NDT data stands as a critical link in evaluating equipment safety. In recent years, object detection techniques have gradually been applied to the analysis of NDT data in pressure equipment inspection, yielding significant results. This paper comprehensively reviews the current applications and development trends of object detection algorithms in NDT technology for pressure-bearing equipment, focusing on algorithm selection, data augmentation, and intelligent defect recognition based on object detection algorithms. Additionally, it explores open research challenges of integrating GAN-based data augmentation and unsupervised learning to further enhance the intelligent application and performance of object detection technology in NDT for pressure-bearing equipment while discussing techniques and methods to improve the interpretability of deep learning models. Finally, by summarizing current research and offering insights for future directions, this paper aims to provide researchers and engineers with a comprehensive perspective to advance the application and development of object detection technology in NDT for pressure-bearing equipment.

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Ultrasonic testing in the field of engineering joining

Cited by 3 publications

References 103 publications

Inspection of Semi-Elliptical Defects in a Steel Pipe Using the Metal Magnetic Memory Method

Inspection of Semi-Elliptical Defects in a Steel Pipe Using the Metal Magnetic Memory Method

Crack Detection Method for Wind Turbine Tower Bolts Using Ultrasonic Spiral Phased Array

Application of Object Detection Algorithms in Non-Destructive Testing of Pressure Equipment: A Review

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