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Proceedings Paper

Using Artificial Neural Networks Approach for the Color Enhance of High Power LEDs
Author(s): Hsi-Chao Chen; Guo-Yang Wu; Chi-Hao Yang; Peng-Ying Chen; Mei-Jyun Lai; Kuo-Ting Huang
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Paper Abstract

High power light-emitting diodes (HP-LEDs) always are applied for energy-saving to replace the traditional light sources. HP-LEDs lighting has been regarded in the next generation lighting. In this study, the RGY colors enhance of whit LED lighting was researched and modulated by artificial neural network (ANN). An ANN model was used to investigate the correlated color temperature (CCT) and luminous flux (Lux) for the white LED enhanced with different power of single RYG LEDs. The starting color temperature of the white LED will be set at 7500K (D75 white light standard), then changed the voltage of the single LED of the red, green or yellow, respectively, to find the best tuning function for the color temperature and luminous efficiency. These results exhibited that changing the voltage of red LED had the broader color temperature from 7500 K to 1500 K than the range of green and yellow LEDs from 7500K to 8200K and 7500K to 4700K, respectively. Then, these experimental results were used as input data for the training model. After the learning model was completed, an analysis was used to obtain the internal representation of the color information by the responses of the individual chips of the three hidden units in the middle layer. Identification rate of data would be achieved to 100% by the neural network pattern-recognition tool. Anyway, the correlation coefficient could reach to 99% by the ANN fitting tool for the color enhancement.

Paper Details

Date Published: 15 October 2012
PDF: 7 pages
Proc. SPIE 8484, Twelfth International Conference on Solid State Lighting and Fourth International Conference on White LEDs and Solid State Lighting, 84841G (15 October 2012); doi: 10.1117/12.929533
Show Author Affiliations
Hsi-Chao Chen, National Yunlin Univ. of Science and Technology (Taiwan)
Dept. of Electronic Engineering, National Yunlin Univ. of Science and Technology, Yunlin (Taiwan)
Graduate School of Science and Technology, National Yunlin Univ. of Science and Technology, Yunlin (Taiwan)
Guo-Yang Wu, National Yunlin Univ. of Science and Technology (Taiwan)
Chi-Hao Yang, National Yunlin Univ. of Science and Technology (Taiwan)
Peng-Ying Chen, National Yunlin Univ. of Science and Technology (Taiwan)
Mei-Jyun Lai, National Yunlin Univ. of Science and Technology (Taiwan)
Kuo-Ting Huang, National Yunlin Univ. of Science and Technology (Taiwan)


Published in SPIE Proceedings Vol. 8484:
Twelfth International Conference on Solid State Lighting and Fourth International Conference on White LEDs and Solid State Lighting
Matthew H. Kane; Christian Wetzel; Jian-Jang Huang; Ian T. Ferguson, Editor(s)

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