Eddy Current Testing in Pipeline Inspection

Reber, Konrad

doi:10.1002/9781119019213.ch36

Cited by 4 publications

(5 citation statements)

References 4 publications

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“…Changes on the far side will affect this bias field, which in turns affects the field measured by the EC sensors. MEC sensors can be incorporated in crawlers, as shown in the MEC Combi Crawler by ( Reber et al, 2016 ). Another example of EC performed by ROVs is shown in ( Antony Jacob et al, 2021 ), where a PEC Probe is mounted to a small ROV in order to measure wall thickness through a layer of marine growth.…”

Section: Inspection Methodsmentioning

confidence: 99%

“…Additionally, crawlers can easily hold a stable distance to the structure, and they can incorporate several tools at once, making them a versatile option. Furthermore, small inspection crawlers, dedicated for the use by ROVs already exist and often have an in build automatic scanning procedure, which might facilitate the incorporation in AUVs ( Jeppesen et al, 2005 ; Reber et al, 2016 ). This requires a compartment to store the crawler, deploy it and handle the connecting fiber autonomously which poses additional soft- and hardware challenges.…”

Section: Requirements For Autonomymentioning

confidence: 99%

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Inspection and maintenance of industrial infrastructure with autonomous underwater robots

Nauert,

Kampmann

2023

Front. Robot. AI

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Underwater infrastructure, such as pipelines, requires regular inspection and maintenance including cleaning, welding of defects and valve-turning or hot-stabbing. At the moment, these tasks are mostly performed by divers and Remotely Operated Vehicles (ROVs) but the use of intervention Autonomous Underwater Vehicles (intervention-AUVs) can greatly reduce operation time, risk, and cost. However, autonomous underwater manipulation has not yet reached a high technological readiness and is an intensively researched topic. This review identifies key requirements based on necessary inspection and maintenance methods, linking them to the current technology and deriving major challenges which need to be addressed in development. These include the handling of tools, where a separation between handheld and mounted tools is detected in already employed underwater intervention vehicles such as the Sabertooth by Saab Seaeye or the Aquanaut by Nauticus robotics, two vehicles capable of semi-autonomous intervention. The main challenge identified concerns high level autonomy, i.e., the process of decision-making. This process includes detecting the correct point of interest, maximizing the workspace of the manipulator, planning the manipulation considering required forces, and monitoring the progress to allow for corrections and high quality results. In order to overcome these issues, reliable close range sensing and precise end point navigation is needed. By identifying these persisting challenges, the paper provides inspiration for further development directions in the field of autonomous underwater intervention.

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Section: Inspection Methodsmentioning

confidence: 99%

Section: Requirements For Autonomymentioning

confidence: 99%

Inspection and maintenance of industrial infrastructure with autonomous underwater robots

Nauert,

Kampmann

2023

Front. Robot. AI

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“…B Nestleroth collected a large number of metal defects of different sizes by means of a pipe detector and investigated the dimensional relationship between the data under the pipe detector and the metal defects [1,2]. Sherbinin studied the relationship between the crack defect depth and the leakage signal, and provided the expected quantification formula for crack characteristics [3,4]. G. Katragadda et al investigated the difference in the leakage magnetic signals of cracks distributed along the entire pipeline circumference and cracks of finite length using the finite element method [5,6].…”

Section: Introductionmentioning

confidence: 99%

Research on the Forward Solving Method of Defect Leakage Signal Based on the Non-Uniform Magnetic Charge Model

Gao

Geng

Yang

et al. 2023

Sensors

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Pipeline magnetic flux leakage inspection is widely used in the evaluation of material defect detection due to its advantages of having no coupling agent and easy implementation. The quantification of defect size is an important part of magnetic flux leakage testing. Defects of different geometrical dimensions produce signal waveforms with different characteristics after excitation. The key to achieving defect quantification is an accurate description of the relationship between the magnetic leakage signal and the size. In this paper, a calculation model for solving the defect leakage field based on the non-uniform magnetic charge distribution of magnetic dipoles is developed. Based on the traditional uniformly distributed magnetic charge model, the magnetic charge density distribution model is improved. Considering the variation of magnetic charge density with different depth positions, the triaxial signal characteristics of the defect are obtained by vector synthesis calculation. Simultaneous design of excitation pulling experiment. The leakage field distribution of rectangular defects with different geometries is analyzed. The experimental results show that the change in defect size will have an impact on the area of the defect leakage field distribution, and the larger the length and wider the width of the defect, the more sensitive the impact on the leakage field distribution. The solution model is consistent with the experimentally obtained leakage signal distribution law, and the model is a practical guide by which to improve the quality of defect evaluation.

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“…It has a deeper penetration depth than radiographic inspection technology, but usually needs to apply coupling agent on the surface, and it is not suitable for the detection of rough surface. Eddy current inspection is based on electromagnetic induction, and uses the secondary eddy current generated by the pipe wall to detect pipeline defects and weld seams [17][18][19][20]. However, due to the skin effect of ferromagnetic materials, the penetration depth decreases with the increase of excitation coil frequency.…”

Section: Introductionmentioning

confidence: 99%

Crosspoint Localization of Spiral and Girth Welds of Spiral Steel Pipelines

Huang

et al. 2020

IEEE Access

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Crosspoint of spiral and girth welds of spiral steel pipelines transporting high-pressure oil and gas is easy to crack due to welding defects and corrosion, so routine excavation and careful inspection are required. In order to reduce the workload and cost of excavation, it is necessary to determine the crosspoint's angular position on the girth weld. This paper proposes a low-cost and high-efficiency method for locating the spiral-girth weld crosspoint based on the inner Spherical Detector (SD). Theoretical analysis and experiments demonstrate that the magnetometer with a smaller lift-off could detect more noticeable magnetic valley of the spiral welds at the pipe bottom, so a smaller SD should be used; the spiral direction can be determined by the phase difference of the dual-channel magnetic signals, when dual magnetometers are symmetrically fixed about the median vertical plane on the rotation axis of the SD. When the girth weld, at least one spiral weld and the spiral direction are detected and determined, the crosspoint's angular position can be calculated. The maximum localization error of the crosspoint is less than 30° and the average error is less than 20°, that is, no more than one hour's angle, whose accuracy is sufficient for excavation and maintenance in the field, because it will reduce the amount of excavation by nearly half.

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Eddy Current Testing in Pipeline Inspection

Cited by 4 publications

References 4 publications

Inspection and maintenance of industrial infrastructure with autonomous underwater robots

Inspection and maintenance of industrial infrastructure with autonomous underwater robots

Research on the Forward Solving Method of Defect Leakage Signal Based on the Non-Uniform Magnetic Charge Model

Crosspoint Localization of Spiral and Girth Welds of Spiral Steel Pipelines

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