A study of the automated eddy current detection of cracks in steel plates

Mohseni, Ehsan and Boukani, Hamid Habibzadeh and Ramos França, Demartonne and Viens, Martin (2020) A study of the automated eddy current detection of cracks in steel plates. Journal of Nondestructive Evaluation, 39 (1). 6. ISSN 0195-9298 (https://doi.org/10.1007/s10921-019-0647-9)

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Abstract

Applying life estimation approaches to determine in-service life of structures and plan the inspection schedules accordingly are becoming acceptable safety design procedures in aerospace. However, these design systems shall be fed with reliable parameters related to material properties, loading conditions and defect characteristics. In this context, the role of non-destructive (NDT) testing reliability is of high importance in detecting and sizing defects. Eddy current test (ECT) is an electromagnetic NDT method frequently used to inspect tiny surface fatigue cracks in sensitive industries. Owing to the new advances in robotic technologies, there is a trend to integrate the ECT into automated systems to perform NDT inspections more efficiently. In fact, ECT can be effectively automated as to increase the coverage, repeatability and scanning speed. The reliability of ECT scanning, however, should be thoroughly investigated and compared to conventional modes of applications to obtain a better understanding of the advantages and shortcomings related to this technique. In this contribution, a series of manual and automated ECT tests are carried out on a set of samples using a split-D reflection differential surface probe. The study investigates the level of noise recorded in each technique and discuss its dependency on different parameters, such as surface roughness and frequency. Afterwards, a description of the effect of crack orientation on ECT signal amplitude is provided through experimental tests and finite element simulations. Finally, the reliability of each ECT technique is investigated by means of probability of detection (POD) curves. POD parameters are then extracted and compared to examine the effect of scanning index, frequency and automation on detection reliability.

ORCID iDs

Mohseni, Ehsan ORCID logoORCID: https://orcid.org/0000-0002-0819-6592, Boukani, Hamid Habibzadeh, Ramos França, Demartonne and Viens, Martin;