Randomized trial investigates parameter selection effects on defect detection in various materials, indicating importance of excitation frequency.
Parameter setting is of paramount importance in pulsed eddy current testing (PECT). However, influenced by multiple relevant factors in technical practice, the setting of specific values involves complex considerations based on the inspection objective. This paper employs dialectics as a methodological framework and uses the detection of globally thinned wall thickness defects in both non-ferromagnetic and ferromagnetic materials as a case study to systematically investigate the rationale underlying the selection of key parameters in PECT. In experiments involving defects in non-ferromagnetic materials, the excitation fundamental frequency maintains stability within a range of roughly three-fourths of the frequency corresponding to the skin depth, and experiences rapid attenuation once it surpasses the threshold. When duty cycle is 50%, the energy percentage of the fundamental frequency is the largest, thereby enabling high detection sensitivity. The dialectical principle of quantitative change leading to qualitative change highlights the nonlinear developmental dynamics. According to this principle, practitioners should focus on nonlinear trends in parameter variations to reinforce the concept of threshold control. In experiments involving defects in ferromagnetic materials, the higher the excitation fundamental frequency selected, the greater the surface eddy current field strength and the higher the detection efficiency, while the eddy current penetration depth decreases. Consequently, in the selection of the excitation fundamental frequency, different strategies should be employed on the basis of the specimen's design thickness (more than 18 mm, less than 12 mm, or between 12–18 mm). The dialectical principle of sublation elucidates the inherent structure of contradictions and the interrelationship between opposing approaches. This principle guides practitioners to conduct specific analyses of multiple complex factors in parameter selection so that they can grasp the main contradiction in parameter selection and enhance their decision-making efficiency.
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Wei et al. (2026) studied this question.
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