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

Kód výsledku v 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>

Nalezeny alternativní kódy

RIV/00216305:26210/26:0198574

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20306 - Audio engineering, reliability analysis

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Theoretical and Applied Fracture Mechanics

ISSN

0167-8442

e-ISSN

1872-7638

Svazek periodika

139

Číslo periodika v rámci svazku

OCT

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

17

Strana od-do

105052

Kód UT WoS článku

001529690300001

EID výsledku v databázi Scopus

2-s2.0-105008976268