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LED junction temperature prediction using machine learning techniques
- Source :
- 2020 IEEE 20th Mediterranean Electrotechnical Conference ( MELECON).
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
-
Abstract
- Light Emitting Diodes (LEDs) are the longest lasting source of artificial illumination whose duration can exceed 50.000 continuous working hours. Nevertheless, they show a gradual reduction of the luminous flux due to the increase of the device temperature. In this work, a Machine Learning algorithm will be introduced and discussed, able to predict the junction temperature value of a LED in real-time while connected in the end-user circuit, taking into account current and voltage flowing in the device and, further, the actual model and aging of the LED. The algorithm was implemented on a microcontroller, showing the feasibility of performing edge machine learning on tiny yet powerful devices.
- Subjects :
- Work (thermodynamics)
Computer science
020209 energy
02 engineering and technology
Edge (geometry)
Machine learning
computer.software_genre
law.invention
Reduction (complexity)
embedded system
law
0202 electrical engineering, electronic engineering, information engineering
business.industry
LED
021001 nanoscience & nanotechnology
Luminous flux
Microcontroller
machine learning
Junction temperature
Artificial intelligence
junction temperature
0210 nano-technology
business
computer
Voltage
Light-emitting diode
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2020 IEEE 20th Mediterranean Electrotechnical Conference ( MELECON)
- Accession number :
- edsair.doi.dedup.....244b0c3e29864ab411315912b8b4966b
- Full Text :
- https://doi.org/10.1109/melecon48756.2020.9140539