「世大智科/天才家居」-我們創業囉
Contact Professor: Yeh-Liang Hsu (徐業良)

九十二學年度元智大學機械工程研究所王耀東碩士論文

Master thesis by Y. T. Wang, Mechanical Engineering Department, Yuan Ze University, 2004

92碩士論文:液晶顯示器之直下型背光光學效能最佳化之研究

  本研究探討液晶顯示器之直下型背光光學效能最佳化設計,藉由幾何尺寸的變數變化來得到直下型背光板在顯示面光學的最大輝度與最佳光學均勻性。本最佳化設計問題有光學輝度的內隱式限制條件及光學均勻性的內隱式目標函數,因此利用序列式類神經網路模擬近似法來求解。
  在序列式類神經網路模擬近似法中首先利用少數訓練資料,訓練二個倒傳遞類神經網路來模擬目標函數及設計點的可行領域,再利用搜尋的演算法在類神經網路的可行領域與目標函數值的領域中搜尋最佳點,這個新的設計點經由Speos光學模擬軟體的計算,得到其目標函數值,並與限制條件比對其可行性。加入這個新的訓練資料後,再一次訓練類神經網路,並重新搜尋更新後的類神經網路。這個過程以迭代的模式運作,直到我們反覆得到相同的設計點,也就是沒有新的訓練點被產生為止。
  本論文中以序列式類神經網路模擬近似法求解了一個2變數及一個4變數的液晶顯示器之直下型背光光學效能最佳化的問題,光學均勻性能顯著提升,且所需光學模擬運算次數也大幅減少。

Optical Efficiency Optimization for a Direct Type Backlight of the Liquid Crystal Display

  This thesis is on optical efficiency optimization for a direct type backlight of the liquid crystal display. The goal is to get the greatest uniformity in a direct type backlight, while the brightness is maintained in a satisfactory level. Both uniformity and brightness are implicit functions that have to be evaluated by optical simulation software Speos. This research will adjust the geometric dimensions, which are discrete design variables, to get the best optical efficiency.
  The Sequential Neural Network Approximation Method (the SNA method) is used in this research. In the SNA method, two back-propagation neural network are trained to simulate the rough maps of the feasible domain and the objective function of this optimization problem using a few representative training data. A search algorithm then searches for the “optimal point” in the feasible domain and the objective function simulated by the neural network. This new design point is simulated by the optical simulation software to check its true objective values and whether it is feasible. This new information is then added to the training set and the neural network is trained again. Then we search for the "optimal point" in this new approximated feasible domain again. This process continues in an iterative manner until the approximate model insists the same "optimal point" in consecutive iterations.
  In this thesis, a two-variable example is used to illustrate the process of SNA. A four-variable optical efficiency optimization problem for a direct type backlight of the liquid crystal display is then solved using the SNA method. In both examples, the number of optical simulations required is greatly reduced.

Academic Thesis
Presentation Files
Last Updated:2010/4/26