| 摘要: | 本研究針對3C使用環境下的工作照明，利用智慧照明燈具來獨立調控中央區域或周圍區域的光源亮度與色溫，進行人因評估實驗。由於電腦及手機螢幕也會發光，我們推論調整燈具中央區的亮暗可以提供使用者較合適的照明。實驗中調整智慧照明燈具之色溫與工作面照度組合出多種照明情境，探討這兩個因子對視覺舒適度、視覺疲勞度及工作績效的影響，再依實驗結果建立智慧照明燈具的控制模型。
人因實驗結果，在客觀指標上工作績效與視覺疲勞度均未達顯著。主觀指標中，中央區、左側讀寫區、前方讀寫區三個工作區域的亮暗程度評分，照度及色溫均為顯著因子。針對中央區、左側讀寫區、前方讀寫區三個區域的主觀亮暗感受建立評分擬合模型，模型預測值與原始資料均高度相關，相關係數分別達0.9436、0.9521、0.9476。接著以三個工作區域評分模型的加權平均，建立燈具整體的評分模型，依照各區域的重要性調配不同的權重，並依據此模型繪出亮暗感受適中的操作區域；考量使用者之間的個體差異，建議以此區域的重心作為燈具的操作點。
;With the rapid development of LED lighting technology, how to effectively manage the lighting systems has become an important topic. Intelligent lighting can be a combination of management and monitoring features that adjusts the output of luminaires spatially or temporally, in order to provide lighting environments with energy efficiency and users’ well-being.
This study focuses on the lighting of a work environment with a computer monitor under an intelligent desk lamp. The lamp has the capability to control the central and outer luminous parts independently. Since the monitor also shines light to the user, we assume dimming the central luminous part would provide better illumination. By adjusting the correlated color temperature (CCT) and central illuminance, psycho- physical experiments are carried out to explore the impact of these two factors on visual comfort, visual fatigue and task performance. Luminaire control models are then established based on the experimental results.
The statistical analyses of the experimental data show that both the CCT and illuminance are not significant factors for the typing speed, typo-finding accuracy and CFF difference, and there is no interaction between the two independent variables. In the subjective assessments, only the brightness and glare perceptions are significantly influenced by the CCT and illuminance, and the other aspects evaluated in the questionnaire are not. The results show that changing the illuminance and CCT will affect the brightness perceptions in all the considered areas, including the central, left, and front reading areas.
To predict the brightness perception of the desk lamp under other operating conditions, the experimental data are used to model the brightness ratings as functions of CCT and illuminance. The R2 measures of goodness of fit are 0.9436, 0.9521 and 0.9476 for the central, left and front areas, respectively. All three R2 values are above 0.7, indicating that the models can well predict the brightness ratings. A weighted control model for the intelligent luminaire is then constructed by using the fitted models in all three areas. The region where the brightness rating is within 5 points plus or minus one standard error of the model is defined as the operating range for proper brightness. To account for user variations, the centroid of this region is our suggested operating point. |
