Detection and quantification of creep strain using process compensated resonance testing (PCRT) sorting modules trained with modeled resonance spectra

Heffernan, Julieanne; Biedermann, Eric; Mayes, Alex; Livings, Richard; Jauriqui, Leanne; Goodlet, Brent; Aldrin, John C.; Mazdiyasni, Siamack

doi:10.1063/1.5031611

Cited by 3 publications

(2 citation statements)

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“…Through the use of various methods (such as X-CT, ultrasound, penetrant testing, microscopic sectioning, operating performance, and operator feedback), the blades were initially labeled into the groups Good or Bad. Through vibrational testing, 6–8 the relevant resonance frequencies, and their associated Q-factors, and amplitudes in the frequency range of [ 3,39 kHz] were obtained. In this study, 15 extracted resonance frequencies are used in MTS, two-stage MCS, and IMCS.…”

Section: Case Study Analysismentioning

confidence: 99%

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Quality inspection of complex-shaped metal parts by vibrations and an integrated Mahalanobis classification system

Cheng

Yaghoubi

Paepegem

et al. 2020

Structural Health Monitoring

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The Mahalanobis–Taguchi system is considered as a promising and powerful tool for handling binary classification cases. Though, the Mahalanobis–Taguchi system has several restrictions in screening useful features and determining the decision boundary in an optimal manner. In this article, an integrated Mahalanobis classification system is proposed which builds on the concept of Mahalanobis distance and its space. The integrated Mahalanobis classification system integrates the decision boundary searching process, based on particle swarm optimizer, directly into the feature selection phase for constructing the Mahalanobis distance space. This integration (a) avoids the need for user-dependent input parameters and (b) improves the classification performance. For the feature selection phase, both the use of binary particle swarm optimizer and binary gravitational search algorithm is investigated. To deal with possible overfitting problems in case of sparse data sets, k-fold cross-validation is considered. The integrated Mahalanobis classification system procedure is benchmarked with the classical Mahalanobis–Taguchi system as well as the recently proposed two-stage Mahalanobis classification system in terms of classification performance. Results are presented on both an experimental case study of complex-shaped metallic turbine blades with various damage types and a synthetic case study of cylindrical dogbone samples with creep and microstructural damage. The results indicate that the proposed integrated Mahalanobis classification system shows good and robust classification performance.

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Section: Case Study Analysismentioning

confidence: 99%

“…For key components with complex shape, such as aircraft engine components or additive manufacturing parts, various non-destructive testing technologies have been developed such as X-ray, ultrasonic testing, radiography, thermal imaging, and vibrational testing. 1–6…”

Section: Introductionmentioning

confidence: 99%