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Volume 11
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10.3390/app11209429
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Article

Empirical Approach to Defect Detection Probability by Acoustic Emission Testing

by
Vera Barat
1,*,
Artem Marchenkov
1,
Valery Ivanov
2,
Vladimir Bardakov
1,3,
Sergey Elizarov
3 and
Alexander Machikhin
1,4
1
Institute of Information Technologies and Computer Science, National Research University “Moscow Power Engineering Institute”, Moscow 111250, Russia
2
Research Department, JSC RII “Spectrum”, Moscow 119048, Russia
3
Research Department, LLC “Interunis-IT”, Moscow 111024, Russia
4
Acousto-optic Spectroscopy Laboratory, Scientific and Technological Center of Unique Instrumentation, Russian Academy of Sciences, Moscow 117342, Russia
*
Author to whom correspondence should be addressed.
Appl. Sci. 2021, 11(20), 9429; https://doi.org/10.3390/app11209429
Submission received: 14 September 2021 / Revised: 7 October 2021 / Accepted: 8 October 2021 / Published: 11 October 2021
(This article belongs to the Special Issue Elastic Waves and Acoustic Emission for Innovative Monitoring of Structures and Engineering Systems)
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Abstract

Estimation of probability of defect detection (POD) is one of the most important problems in acoustic emission (AE) testing. It is caused by the influence of the material microstructure parameters on the diagnostic data, variability of noises, the ambiguous assessment of the materials emissivity, and other factors, which hamper modeling the AE data, as well as the a priori determination of the diagnostic parameters necessary for calculating POD. In this study, we propose an empirical approach based on the generalization of the experimental AE data acquired under mechanical testing of samples to a priori estimation of the AE signals emitted by the defect. We have studied the samples of common industrial steels 09G2S (similar to steel ANSI A 516-55) and 45 (similar to steel 1045) with fatigue cracks grown in laboratory conditions during cyclic testing. Empirical generalization of data using probabilistic models enables estimating the conditional probability of record emissivity and amplitudes of AE signals. This approach allows to eliminate the existing methodological gap and to build a comprehensive method for assessing the probability of fatigue cracks detection by the AE testing.
Keywords: non-destructive testing; acoustic emission; probability of defect detection; fatigue cracks non-destructive testing; acoustic emission; probability of defect detection; fatigue cracks

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MDPI and ACS Style

Barat, V.; Marchenkov, A.; Ivanov, V.; Bardakov, V.; Elizarov, S.; Machikhin, A. Empirical Approach to Defect Detection Probability by Acoustic Emission Testing. Appl. Sci. 2021, 11, 9429. https://doi.org/10.3390/app11209429

AMA Style

Barat V, Marchenkov A, Ivanov V, Bardakov V, Elizarov S, Machikhin A. Empirical Approach to Defect Detection Probability by Acoustic Emission Testing. Applied Sciences. 2021; 11(20):9429. https://doi.org/10.3390/app11209429

Chicago/Turabian Style

Barat, Vera, Artem Marchenkov, Valery Ivanov, Vladimir Bardakov, Sergey Elizarov, and Alexander Machikhin. 2021. "Empirical Approach to Defect Detection Probability by Acoustic Emission Testing" Applied Sciences 11, no. 20: 9429. https://doi.org/10.3390/app11209429

APA Style

Barat, V., Marchenkov, A., Ivanov, V., Bardakov, V., Elizarov, S., & Machikhin, A. (2021). Empirical Approach to Defect Detection Probability by Acoustic Emission Testing. Applied Sciences, 11(20), 9429. https://doi.org/10.3390/app11209429

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