Damage detection by recurrence and entropy methods on the basis of time series measured during composite milling
Artykuł w czasopiśmie
MNiSW
100
Lista 2021
Status: | |
Autorzy: | Kęcik Krzysztof, Ciecieląg Krzysztof, Zaleski Kazimierz |
Dyscypliny: | |
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Rok wydania: | 2020 |
Wersja dokumentu: | Drukowana | Elektroniczna |
Język: | angielski |
Numer czasopisma: | 1-2 |
Wolumen/Tom: | 111 |
Strony: | 549 - 563 |
Impact Factor: | 3,226 |
Web of Science® Times Cited: | 20 |
Scopus® Cytowania: | 20 |
Bazy: | Web of Science | Scopus |
Efekt badań statutowych | NIE |
Finansowanie: | The project/research was financed in the framework of the project Lublin University of Technology - Regional Excellence Initiative, funded by the Polish Ministry of Science and Higher Education (contract no. 030/RID/2018/19 ). |
Materiał konferencyjny: | NIE |
Publikacja OA: | TAK |
Licencja: | |
Sposób udostępnienia: | Witryna wydawcy |
Wersja tekstu: | Ostateczna wersja opublikowana |
Czas opublikowania: | Przed opublikowaniem |
Data opublikowania w OA: | 30 września 2020 |
Abstrakty: | angielski |
This paper presents methods for damage detection in machined material on the basis of time series measured during milling of glass-fiber–reinforced polymer (GFRP). Recurrence methods and different types of entropy have emerged as useful tools for detecting subtle non-stationarities and/or changes in nonlinear signals. In this research, a recurrence plot, recurrence quantifications, an approximate entropy, and sample entropy are used. By identifying changes in the cutting force measured during the composite milling process, the damage occurrence has been detected. Firstly, the damage has been modelled as the intentionally introduced hole with different diameters and depths in order to estimate the size detectable damages and to select proper recurrence measures as damage indicators. Next, the experiments with the real damage have been performed and the damage indicators have used. |