Investigation of signal features of pulsed eddy current testing technique by experiments

2013 ◽  
Vol 55 (9) ◽  
pp. 487-491 ◽  
Author(s):  
Yu Yating ◽  
Guan Jia
Keyword(s):  
Eddy Current ◽  
Eddy Current Testing ◽  
Testing Technique ◽  
Current Testing ◽  
Pulsed Eddy Current ◽  
Signal Features

Probabilistic evaluation of detection capability of eddy current testing to inspect pitting on a stainless steel clad using multiple signal features

2020 ◽  
Vol 64 (1-4) ◽  
pp. 47-55
Author(s):  
Takuma Tomizawa ◽  
Haicheng Song ◽  
Noritaka Yusa
Keyword(s):  
Stainless Steel ◽  
Eddy Current ◽  
Pressure Vessels ◽  
Eddy Current Testing ◽  
Probability Of Detection ◽  
Current Testing ◽  
Multiple Signal ◽  
Signal Features ◽  
Inner Surface ◽  
Drill Holes

This study proposes a probability of detection (POD) model to quantitatively evaluate the capability of eddy current testing to detect flaws on the inner surface of pressure vessels cladded by stainless steel and in the presence of high noise level. Welded plate samples with drill holes were prepared to simulate corrosion that typically appears on the inner surface of large-scale pressure vessels. The signals generated by the drill holes and the noise caused by the weld were examined using eddy current testing. A hit/miss-based POD model with multiple flaw parameters and multiple signal features was proposed to analyze the measured signals. It is shown that the proposed model is able to more reasonably characterize the detectability of eddy current signals compared to conventional models that consider a single signal feature.

scholarly journals Evaluation of Coating Thickness Using Lift-Off Insensitivity of Eddy Current Sensor

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 419
Author(s):  
Xiaobai Meng ◽  
Mingyang Lu ◽  
Wuliang Yin ◽  
Abdeldjalil Bennecer ◽  
Katherine J. Kirk
Keyword(s):  
Eddy Current ◽  
Coating Thickness ◽  
Thickness Measurement ◽  
Eddy Current Testing ◽  
Thickness Variation ◽  
Testing Technique ◽  
Current Testing ◽  
Thin Skin ◽  
Embedded Algorithms ◽  
Lift Off

Defect detection in ferromagnetic substrates is often hampered by nonmagnetic coating thickness variation when using conventional eddy current testing technique. The lift-off distance between the sample and the sensor is one of the main obstacles for the thickness measurement of nonmagnetic coatings on ferromagnetic substrates when using the eddy current testing technique. Based on the eddy current thin-skin effect and the lift-off insensitive inductance (LII), a simplified iterative algorithm is proposed for reducing the lift-off variation effect using a multifrequency sensor. Compared to the previous techniques on compensating the lift-off error (e.g., the lift-off point of intersection) while retrieving the thickness, the simplified inductance algorithms avoid the computation burden of integration, which are used as embedded algorithms for the online retrieval of lift-offs via each frequency channel. The LII is determined by the dimension and geometry of the sensor, thus eliminating the need for empirical calibration. The method is validated by means of experimental measurements of the inductance of coatings with different materials and thicknesses on ferrous substrates (dual-phase alloy). The error of the calculated coating thickness has been controlled to within 3% for an extended lift-off range of up to 10 mm.

scholarly journals Defect detection in conducting materials using eddy current testing techniques

2014 ◽  
Vol 11 (4) ◽  
pp. 535-549 ◽  
Author(s):  
Hartmut Brauer ◽  
Marek Ziolkowski ◽  
Hannes Toepfer
Keyword(s):  
Eddy Current ◽  
Eddy Current Testing ◽  
Internal Defects ◽  
Testing Technique ◽  
Defect Identification ◽  
Testing Conditions ◽  
Current Testing ◽  
Conducting Materials ◽  
Testing Techniques ◽  
Electrical Conductors

Lorentz force eddy current testing (LET) is a novel nondestructive testing technique which can be applied preferably to the identification of internal defects in nonmagnetic moving conductors. The LET is compared (similar testing conditions) with the classical eddy current testing (ECT). Numerical FEM simulations have been performed to analyze the measurements as well as the identification of internal defects in nonmagnetic conductors. The results are compared with measurements to test the feasibility of defect identification. Finally, the use of LET measurements to estimate of the electrical conductors under test are described as well.

scholarly journals The Effects of Lift-Off from Wall Thinning Signal in Pulsed Eddy Current Testing

2012 ◽  
Vol 17 (4) ◽  
pp. 298-301 ◽  
Author(s):  
Duck-Gun Park ◽  
C.S. Angani ◽  
M.B. Kishore ◽  
C.G. Kim ◽  
D.H. Lee
Keyword(s):  
Eddy Current ◽  
Eddy Current Testing ◽  
Current Testing ◽  
Pulsed Eddy Current ◽  
Wall Thinning ◽  
Lift Off

scholarly journals Evaluation of Coating Thickness Using Lift-Off Insensitivity of Eddy Current Sensor

2021 ◽  
Author(s):  
Xiaobai Meng ◽  
Mingyang Lu ◽  
Wuliang Yin ◽  
Abdeldjalil Bennecer ◽  
Katherine Kirk
Keyword(s):  
Eddy Current ◽  
Coating Thickness ◽  
Thickness Measurement ◽  
Eddy Current Testing ◽  
Thickness Variation ◽  
Testing Technique ◽  
Current Testing ◽  
Thin Skin ◽  
Embedded Algorithms ◽  
Lift Off

Defect detection in ferromagnetic substrates is often hampered by non-magnetic coating thickness variation when using conventional eddy current testing technique. The lift-off distance between the sample and the sensor is one of the main obstacles for the thickness measurement of non-magnetic coatings on ferromagnetic substrates when using the eddy current testing technique. Based on the eddy current thin-skin effect and the lift-off insensitive inductance (LII), a simplified iterative algorithm is proposed for reducing the lift-off variation effect using a multi-frequency sensor. Compared to the previous techniques on compensating the lift-off error (e.g., the lift-off point of intersection) while retrieving the thickness, the simplified inductance algorithms avoid the computation burden of integration, which are used as embedded algorithms for the online retrieval of lift-offs via each frequency channel. The LII is determined by the dimension and geometry of the sensor, thus eliminating the need for empirical calibration. The method is validated by means of experimental measurements of the inductance of coatings with different materials and thicknesses on ferrous substrates (dual-phase alloy). The error of the calculated coating thickness has been controlled to within 3 % for an extended lift-off range of up to 10 mm.

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