Optimization of optical design for developing an LED lens module

被引:9
作者
Chen, Wen-Chin [1 ]
Liu, Kai-Ping [2 ]
Liu, Binghui [3 ]
Lai, Tung-Tsan [2 ]
机构
[1] Chung Hua Univ, Dept Ind Management, Hsinchu 30012, Taiwan
[2] Chung Hua Univ, PhD Program Technol Management, Hsinchu 30012, Taiwan
[3] Xiamen Univ Technol, Dept Management Sci, Xiamen, Peoples R China
关键词
LED lens module; ANOVA; Orthogonal arrays; Back-propagation neural network; Genetic algorithms; Particle swarm optimization;
D O I
10.1007/s00521-012-0990-6
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this study, a procedure for optimization of an LED lens module design based on 3 LED light sources was divided into two phases. For preliminary optimization of the dimensions of the LED lens module in Stage I, an optical analysis with orthogonal arrays and TracePro (an optical design package) combined with analysis of variance was conducted to investigate relationships between the multiple optical quality characteristics (viewing angle and average illuminance) and dimension parameters and find the initial optimal parameter combination of the LED lens module. In Stage II, the initial optimal parameter combination determined in Stage I was employed to develop an orthogonal array L-25(5(6)) for optical simulation. The experimental data of the orthogonal array were used to train and test the back-propagation neural network to develop an optical quality predictor, which was integrated into the genetic algorithms and the particle swarm optimization in order to find the optimal parameter combination that conformed to optical quality. From the experimental results, the proposed optimization procedure contributes to a precise viewing angle to achieve the goal of optical quality and improved the average illuminance in development of the product. The procedure to optimize the optical design developed in this study can be applied to design all types of LED lens modules and improve the optical design and technology of the LED lens industry.
引用
收藏
页码:811 / 823
页数:13
相关论文
共 9 条
[1]   An optimization system for LED lens design [J].
Chen, Wen-Chin ;
Lai, Tung-Tsan ;
Wang, Min-Wen ;
Hung, Hsiao-Wen .
EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (09) :11976-11983
[2]   An integrated parameter optimization system for MISO plastic injection molding [J].
Chen, Wen-Chin ;
Wang, Min-Wen ;
Chen, Chen-Tai ;
Fu, Gong-Loung .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2009, 44 (5-6) :501-511
[3]   Multi-objective design and extended optimization for developing a miniature light emitting diode pocket-sized projection display [J].
Fang, Yi-Chin ;
Tzeng, Yih-Fong ;
Li, Si-Xian .
OPTICAL REVIEW, 2008, 15 (05) :241-250
[4]   A new multi-gene genetic programming approach to nonlinear system modeling. Part I: materials and structural engineering problems [J].
Gandomi, Amir Hossein ;
Alavi, Amir Hossein .
NEURAL COMPUTING & APPLICATIONS, 2012, 21 (01) :171-187
[5]   Study of optimization of an LCD light guide plate with neural network and genetic algorithm [J].
Li, Chen-Jung ;
Fang, Yi-Chin ;
Cheng, Ming-Chia .
OPTICS EXPRESS, 2009, 17 (12) :10177-10188
[6]   Effects on illumination uniformity due to dilution on arrays of LEDs [J].
Moreno, I ;
Tzonchev, RI .
NONIMAGING OPTICS AND EFFICIENT ILLUMINATION SYSTEMS, 2004, 5529 :268-275
[7]  
Parkyn WA, 2005, INT SOC OPT ENG C SP, V5942, P1
[8]   Prediction of power output of a coal-fired power plant by artificial neural network [J].
Smrekar, J. ;
Pandit, D. ;
Fast, M. ;
Assadi, M. ;
De, Sudipta .
NEURAL COMPUTING & APPLICATIONS, 2010, 19 (05) :725-740
[9]   Designing MIMO controller by neuro-traveling particle swarm optimizer approach [J].
Su, Chwen-Tzeng ;
Wong, Jui-Tsung .
EXPERT SYSTEMS WITH APPLICATIONS, 2007, 32 (03) :848-855