Machine-Learning Assisted Prediction of Spectral Power Distribution for Full-Spectrum White Light-Emitting Diode

Abstract

The full-spectrum white light-emitting diode (LED) emits light with a broad wavelength range by mixing all lights from multiple LED chips and phosphors. Thus, it has great potentials to be used in healthy lighting, high resolution displays, plant lighting with higher color rendering index close to sunlight and higher color fidelity index. The spectral power distribution (SPD) of light source, representing its light quality, is always dynamically controlled by complex electrical and thermal loadings when the light source operates under usage conditions. Therefore, a dynamic prediction of SPD for the full-spectrum white LED has become a hot but challenging research topic in the high quality lighting design and application. This paper proposes a dynamic SPD prediction method for the full-spectrum white LED by integrating the SPD decomposition approach with the artificial neural network (ANN) based machine learning method. Firstly, the continuous SPDs of a full-spectrum white LED driven by an electrical-thermal loading matrix are discretized by the multi-peak fitting with Gaussian model as the relevant spectral characteristic parameters. Then, the Back Propagation (BP) and Genetic Algorithm-Back Propagation (GA-BP) NNs are proposed to predict the spectral characteristic parameters of LEDs operated under any usage conditions. Finally, the dynamically predicted spectral characteristic parameters are used to reconstruct the SPDs. The results show that: (1) The spectral characteristic parameters obtained by fitting with the Gaussian model can be used to represent the emission lights from multiple chips and phosphors in a full-spectrum white LED; (2) The prediction errors of both BP NN and GA-BP NN can be controlled at low level, that is to say, our proposed method can achieve a highly accurate SPD dynamic prediction for the full-spectrum white LED when it operates under different operation mission profiles.

Rare‐Earth‐Based Perovskite Cs2AgScCl6:Bi for Strong Full Visible Spectrum Emission

“…[9][10][11] Up to now, the most common solution for white LED (WLED) is to integrate the spectrum with polychromatic phosphors (red, green, and yellow) requiring multiple optical materials and procedures, which are low efficiency and high costs. [12][13][14] Therefore, it is urgent to develop high-efficiency and full-spectrum white emission materials.…”

Phosphor-Converted Laser-Based Illuminant With High Color Rendering Index and Low Blue Light Hazard

“…To improve the CRI of pc-LBI, the spectral power distribution of emission spectrum from pc-LBI and red LDs is considered. We assumed that the peak wavelength and FWHM of blue LDs and red LDs are constant [37,38]. So, the spectral power distribution of emissive pc-LBI will be linearly combined with the spectral power distribution of red emissive parts.…”

Investigation on Circadian Action and Color Quality in Laser-Based Illuminant for General Lighting and Display

“…Solid-State lighting is one of the most promising lighting technologies in the 21st century, and has become the dominant technology for the general lighting [1]. The solid-state lighting technology based on light-emitting diodes (LEDs) and laser diodes (LDs) has gained widespread attention [2], [3]. In recent years, LEDs are replacing conventional incandescent lamps due to several well-known advantages, such as color-tunable property, long lifespan, compact size, and high luminous efficacy among others [4], [5].…”