An approach to analyse of LED degradation heterogeneity in step-stress accelerated testing
Artykuł w czasopiśmie
MNiSW
140
Lista 2024
| Status: | |
| Autorzy: | La Quoc Tiep, Vališ David, Vintr Zdeněk, Gajewski Jakub, Žák Libor, Kohl Zdeněk, Cu Zixuan Phong |
| Dyscypliny: | |
| Aby zobaczyć szczegóły należy się zalogować. | |
| Rok wydania: | 2026 |
| Wersja dokumentu: | Drukowana | Elektroniczna |
| Język: | angielski |
| Numer czasopisma: | 3 |
| Wolumen/Tom: | 28 |
| Strony: | 1 - 21 |
| Impact Factor: | 3,1 |
| Bazy: | BazTech |
| Efekt badań statutowych | NIE |
| Finansowanie: | This article has been prepared with support of the University of Defence, Brno, Czech Republic and in particular the “Partial development intention funding” VAROPS |
| Materiał konferencyjny: | NIE |
| Publikacja OA: | TAK |
| Licencja: | |
| Sposób udostępnienia: | Otwarte czasopismo |
| Wersja tekstu: | Ostateczna wersja opublikowana |
| Czas opublikowania: | W momencie opublikowania |
| Data opublikowania w OA: | 18 lutego 2026 |
| Abstrakty: | angielski |
| Light-emitting diodes (LEDs) have become indispensable in modern applications owing to their high energy efficiency, long lifespan, and robustness compared to conventional light sources. Given these attributes, the reliability of LEDs has become a crucial factor, directly influencing the ability of systems and devices to perform their intended functions over time. However, variations in materials, structures, and manufacturing processes introduce heterogeneity in their degradation behaviour, even under identical operating conditions. In applications demanding brightness stability, colour rendering, and reliability prediction, degradation homogeneity is crucial, making the analysis of LED heterogeneity essential. This article investigates such heterogeneity using feature extraction methods, kernel density estimation, and divergence measures based on degradation data obtained from optimized step-stress accelerated tests. The proposed approach is used to quantify and evaluate LED degradation variability and has clear implications for reliability assessment and predictive modelling. |
