| Autor: |
Truong, Minh-Tuan, Mendizabal, Laurent, Do Van, Phuc, Iung, Benoît |
| Přispěvatelé: |
Centre de Recherche en Automatique de Nancy (CRAN), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Commissariat à l'énergie atomique et aux énergies alternatives - Laboratoire d'Electronique et de Technologie de l'Information (CEA-LETI), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA) |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
2022 10th International Conference on Systems and Control (ICSC). |
| DOI: |
10.1109/icsc57768.2022.9993909 |
| Popis: |
International audience; Constant-stress Accelerated Degradation Testing (ADT) has become a common method to get degradation data of components/systems. The ADT design aims to build an optimal ADT plan under specific constraints, e.g., limited test resources. Bayesian optimal design is a method of decision theory under uncertainty, which uses historical data and expert information to find the optimal test plan. In this paper, we develop a Bayesian-based approach for optimizing ADT plan of a LED component considering the self-heating phenomenon. In that way, D-optimal is used as a main criterion to find the optimal ADT plan under limited resources. Experimental data from LED components demonstrate the proposed method. The obtained results highlight the robustness and performance of the proposed approach. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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