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Bayesian Hierarchical Modelling for Uncertainty Quantification in Operational Thermal Resistance of LED Systems

التفاصيل البيبلوغرافية
العنوان: Bayesian Hierarchical Modelling for Uncertainty Quantification in Operational Thermal Resistance of LED Systems
المؤلفون: Michaela Dvorzak, Julien Magnien, Ulrike Kleb, Elke Kraker, Manfred Mücke
المصدر: Applied Sciences, Vol 12, Iss 19, p 10063 (2022)
بيانات النشر: MDPI AG, 2022.
سنة النشر: 2022
المجموعة: LCC:Technology
LCC:Engineering (General). Civil engineering (General)
LCC:Biology (General)
LCC:Physics
LCC:Chemistry
مصطلحات موضوعية: LED system, uncertainty quantification, remaining useful life, thermal resistance, power cycling, Bayesian hierarchical modelling, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
الوصف: Remaining useful life (RUL) prediction is central to prognostics and reliability assessment of light-emitting diode (LED) systems. Their unknown long-term service life remaining when subject to specific operating conditions is affected by various sources of uncertainty stemming from production of individual system components, application of the whole system, measurement and operation. To enhance the reliability of model-based predictions, it is essential to account for all of these uncertainties in a systematic manner. This paper proposes a Bayesian hierarchical modelling framework for inverse uncertainty quantification (UQ) in LED operation under thermal loading. The main focus is on the LED systems’ operational thermal resistances, which are subject to system and application variability. Posterior inference is based on a Markov chain Monte Carlo (MCMC) sampling scheme using the Metropolis–Hastings (MH) algorithm. Performance of the method is investigated for simulated data, which allow to focus on different UQ aspects in applications. Findings from an application scenario in which the impact of disregarded uncertainty on RUL prediction is discussed highlight the need for a comprehensive UQ to allow for reliable predictions.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2076-3417
Relation: https://www.mdpi.com/2076-3417/12/19/10063; https://doaj.org/toc/2076-3417
DOI: 10.3390/app121910063
URL الوصول: https://doaj.org/article/b7fa496d1a044a929aa665df023eadee
رقم الأكسشن: edsdoj.b7fa496d1a044a929aa665df023eadee
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20763417
DOI:10.3390/app121910063