Lifetime Prediction for a Cell-on-Board (COB) Light Source Based on the Adaptive Neuro-Fuzzy Inference System (ANFIS)

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dc.authoridKIYAK, Ismail/0000-0002-5061-6378
dc.authorwosidGökmen, Gökhan/AAG-6655-2020
dc.contributor.authorKiyak, Ismail
dc.contributor.authorGokmen, Gokhan
dc.contributor.authorKocyigit, Gokhan
dc.date.accessioned2024-06-12T11:20:04Z
dc.date.available2024-06-12T11:20:04Z
dc.date.issued2021
dc.departmentTrakya Üniversitesien_US
dc.description.abstractPredicting the lifetime of a LED lighting system is important for the implementation of design specifications and comparative analysis of the financial competition of various illuminating systems. Most lifetime information published by LED manufacturers and standardization organizations is limited to certain temperature and current values. However, as a result of different working and ambient conditions throughout the whole operating period, significant differences in lifetimes can be observed. In this article, an advanced method of lifetime prediction is proposed considering the initial task areas and the statistical characteristics of the study values obtained in the accelerated fragmentation test. This study proposes a new method to predict the lifetime of COB LED using an artificial intelligence approach and LM-80 data. Accordingly, a database with 6000 hours of LM-80 data was created using the Neuro-Fuzzy (ANFIS) algorithm, and a highly accurate lifetime prediction method was developed. This method reveals an approximate similarity of 99.8506% with the benchmark lifetime. The proposed methodology may provide a useful guideline to lifetime predictions of LED-related products which can also be adapted to different operating conditions in a shorter time compared to conventional methods. At the same time, this method can be used in the life prediction of nanosensors and can be produced with the 3D technique.en_US
dc.identifier.doi10.1155/2021/6681335
dc.identifier.issn1687-4110
dc.identifier.issn1687-4129
dc.identifier.scopus2-s2.0-85104772970en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.1155/2021/6681335
dc.identifier.urihttps://hdl.handle.net/20.500.14551/25459
dc.identifier.volume2021en_US
dc.identifier.wosWOS:000640314900001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherHindawi Ltden_US
dc.relation.ispartofJournal Of Nanomaterialsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectThermal-Analysisen_US
dc.subjectLed Lampsen_US
dc.titleLifetime Prediction for a Cell-on-Board (COB) Light Source Based on the Adaptive Neuro-Fuzzy Inference System (ANFIS)en_US
dc.typeArticleen_US

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