Lifetime Prediction for a Cell-on-Board (COB) Light Source Based on the Adaptive Neuro-Fuzzy Inference System (ANFIS)
| Autor: | Gökhan Koçyiğit, Gökhan Gökmen, Ismail Kiyak |
|---|---|
| Přispěvatelé: | Kiyak, Ismail, Gokmen, Gokhan, Kocyigit, Gokhan |
| Rok vydání: | 2021 |
| Předmět: |
010302 applied physics
Adaptive neuro fuzzy inference system Similarity (geometry) Materials science Article Subject Standardization 020209 energy 02 engineering and technology 01 natural sciences law.invention Task (project management) Market fragmentation Reliability engineering LED lamp Light source law 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Benchmark (computing) T1-995 General Materials Science Technology (General) |
| Zdroj: | Journal of Nanomaterials, Vol 2021 (2021) |
| ISSN: | 1687-4129 1687-4110 |
| Popis: | Predicting 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. |
| Databáze: | OpenAIRE |
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