Computational Simulation of a Non-Destructive Testing Technique for Steel Bar Sizing in Concrete Structures using Eddy Current Testing and Neural Networks

2010 ◽  
Author(s):  
N.P. de Alcantara Jr ◽  
T. Marques ◽  
D.C. Costa ◽  
D. Guedes ◽  
G.P. Sanchis ◽  
...  
Keyword(s):  
Neural Networks ◽  
Eddy Current ◽  
Computational Simulation ◽  
Eddy Current Testing ◽  
Non Destructive Testing ◽  
Destructive Testing ◽  
Testing Technique ◽  
Current Testing ◽  
Steel Bar ◽  
Non Destructive

scholarly journals Physic perspective fusion of electromagnetic acoustic transducer and pulsed eddy current testing in non-destructive testing system

2020 ◽  
Vol 378 (2182) ◽  
pp. 20190608
Author(s):  
Wei Guo ◽  
Bin Gao ◽  
Gui Yun Tian ◽  
Dan Si
Keyword(s):  
Eddy Current ◽  
Surface Defects ◽  
Eddy Current Testing ◽  
Non Destructive Testing ◽  
Electromagnetic Acoustic Transducer ◽  
Destructive Testing ◽  
Current Testing ◽  
Pulsed Eddy Current ◽  
Acoustic Transducer ◽  
Non Destructive

Comprehensive non-destructive testing (NDT) for pipelines is a critical and challenging task. This paper proposes a novel physic perspective fusion NDT method of electromagnetic acoustic transducer (EMAT) and pulsed Eddy current testing (PECT) for detecting hybrid defects. This transceiver-integrated fusion sensor structure can simultaneously excite ultrasound and pulsed eddy current. Therefore, the generated ultrasound is applied to detect deep defects, while the eddy current detects surface defects. The theoretical derivation of EMAT and PECT fusion mechanism has been developed for analysis and interpretation of the results. In addition, numerical simulation on the detection of hybrid defects including surface defects with different width, depth and multiple bottom-thinning defects has been conducted. Experiments on both ferromagnetic and non-ferromagnetic material verify the feasibility of composite detection. Finally, tests have been validated on pipeline with weld defects, and the results show that the composite inspection method is capable of monitoring thickness variations and inspecting surface defects. This article is part of the theme issue ‘Advanced electromagnetic non-destructive evaluation and smart monitoring’.

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