LED智能光源混光呈色模型构建方法研究

LED智能光源具有色光可调的特点，其内置微处理系统可以通过无线数据传输等技术调整发光方式，控制光色及发光强度，进而实现照明光源的动态调节，因此特别适合于博物馆展陈、家居照明等智能化照明设计环节。现阶段，鉴于LED光源智能混光技术尚未普及，目前绝大多数商用LED智能光源在混光控制方面仅局限于设备制造商所设定的几类固定模式，无法充分发挥智能LED光源色光可调的技术优势。针对此问题，提出了一种基于BP神经网络以及有效集算法的LED智能光源混光呈色模型构建方法，实现了LED智能光源控制信号与对应发光光谱辐亮度分布之间的双向高精度映射。研究中首先提出了一种基于BP神经网络的LED混光呈色预测方法，实现了由LED智能光源驱动控制值向光源实际发光光谱辐亮度分布的准确预测;在此基础上运用有效集算法实现了由光源实际发光光谱辐亮度分布向LED智能光源驱动控制值的反向高精度预测。实验结果显示，所提出的方法整体建模误差显著小于人眼视觉可分辨阈值(CIEUCS Duv值可低至0.002 7)，达到了较为理想的建模效果。该方法的提出，将为当前LED智能光源制造以及现有商用LED智能光源的二次开发与优化提供有效的理论与方法支撑。

Research on the Development of Light Blending Model for Smart LED Lighting

The color of the LED smart light is tunable by its inner equipped micro-processing systems.Therefore,it could pro-vide significant improvement for the smart lighting conditions,such as museum lighting and home lighting.At present,the limi-tation of the current lighting blending technology remarkably affects the application of smart lighting technology and people could not make full use of the adj ustability of the smart luminaries.In this research,a novel light blending model was proposed based on BP neural network and active set algorithm.The models could effectively simulate the nonlinear relationship between the de-vice control values of the smart light and the output radiance spectrum of the light.Particularly,a BP neural network-based for-ward model for LED light blending was firstly proposed,which could accurately calculate the spectral radiance power distribution from the device control values.Afterwards,based on forward model,an active set algorithm-based backward model was devel-oped,which could precisely predict the device control values from the desired spectral radiance power distribution.The experi-mental result indicates that the proposed method could accurately achieve the light blending controlling of smart LED light,with a CIEUCS Duv value of 0.002 7,which is significantly smaller than the just noticeable difference value of human vision.The au-thors believe that the proposed method will provided effective support for the development of smart LED lighting in near future.