Inflection point principle combined with digital image correlation and machine learning for crack length measurement in fatigue tests

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081723%3A_____%2F25%3A00637615" target="_blank" >RIV/68081723:_____/25:00637615 - isvavai.cz</a>
Alternative codes found
RIV/00216305:26210/26:0198574
Result on the web
<a href="https://www.webofscience.com/wos/woscc/full-record/WOS:001529690300001" target="_blank" >https://www.webofscience.com/wos/woscc/full-record/WOS:001529690300001</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.tafmec.2025.105052" target="_blank" >10.1016/j.tafmec.2025.105052</a>

Result language
angličtina
Original language name
Inflection point principle combined with digital image correlation and machine learning for crack length measurement in fatigue tests
Original language description
The visual inspection method is a widely used non-contact technique for measuring fatigue crack propagation, but it is inefficient, requiring frequent operator input. Digital image correlation (DIC) methods provide alternatives. However, full-field methods are computationally demanding, while line-based thresholding techniques are sensitive to material load conditions, reducing consistency. This study proposes and validates a new non-contact, physically-based method for real-time crack length evaluation. It eliminates the need for thresholding and enables higher testing frequencies due to its line-based nature, supporting accurate, versatile, and automated fatigue testing. The method integrates the inflection point principle with DIC and machine learning. Visual inspection serves as a validation baseline, using a novel setup that applies both methods simultaneously on the same side of the sample for direct comparison. The proposed method shows good agreement with baseline results, achieving mean absolute errors of 24 mu m (static) and 54 mu m (dynamic). Compared to line-based thresholding, it is four times more accurate (dynamic) and independent of load levels, though 1.7 times slower.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20306 - Audio engineering, reliability analysis

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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