Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/91364
| Title: | Prognostics of radiation power degradation lifetime for ultraviolet light-emitting diodes using stochastic data-driven models | Authors: | Fan, J Jing, Z Cao, Y Ibrahim, MS Li, M Fan, X Zhang, G |
Issue Date: | Jun-2021 | Source: | Energy and AI, June 2021, v. 4, 100066 | Abstract: | With their advantages of high efficiency, long lifetime, compact size and being free of mercury, ultraviolet light-emitting diodes (UV LEDs) are widely applied in disinfection and purification, photolithography, curing and biomedical devices. However, it is challenging to assess the reliability of UV LEDs based on the traditional life test or even the accelerated life test. In this paper, radiation power degradation modeling is proposed to estimate the lifetime of UV LEDs under both constant stress and step stress degradation tests. Stochastic data-driven predictions with both Gamma process and Wiener process methods are implemented, and the degradation mechanisms occurring under different aging conditions are also analyzed. The results show that, compared to least squares regression in the IESNA TM-21 industry standard recommended by the Illuminating Engineering Society of North America (IESNA), the proposed stochastic data-driven methods can predict the lifetime with high accuracy and narrow confidence intervals, which confirms that they provide more reliable information than the IESNA TM-21 standard with greater robustness. | Keywords: | Degradation modeling Gamma process IESNA TM-21 Ultraviolet light-emitting diodes (UV LEDs) Wiener process |
Publisher: | Elsevier BV | Journal: | Energy and AI | EISSN: | 2666-5468 | DOI: | 10.1016/j.egyai.2021.100066 | Rights: | © 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/) The following publication Fan, J., Jing, Z., Cao, Y., Ibrahim, M. S., Li, M., Fan, X., & Zhang, G. (2021). Prognostics of radiation power degradation lifetime for ultraviolet light-emitting diodes using stochastic data-driven models. Energy and AI, 4, 100066 is available at https://doi.org/10.1016/j.egyai.2021.100066 |
| Appears in Collections: | Journal/Magazine Article |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 1-s2.0-S2666546821000203-main.pdf | 3.5 MB | Adobe PDF | View/Open |
Access
View full-text via PolyU eLinks 
Page views
13
Last Week
2
2
Last month
Citations as of May 28, 2023
Downloads
9
Citations as of May 28, 2023
SCOPUSTM
Citations
2
Citations as of May 25, 2023
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.