Improving Peak-Wavelength Method to Measure Junction Temperature by Dual-Wavelength LEDs

Zhao, Yukun; Yun, Feng; Feng, Lishuang; Wang, Shuai; Li, Yufeng; Su, Xilin; Guo, Minghui; Ding, Wen; Zhang, Ye

doi:10.1109/access.2017.2716781

Cited by 8 publications

(8 citation statements)

References 19 publications

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“…Robustness has been tested by systematically and individually shifting, after neural network training, each of the 12 system function parameters over a ± 4 nm range in steps of 1 nm and calculating the mean RMSE values for the Macbeth data set using the shifted system functions. Note that 4 nm wavelength shifts correspond to about 70 K and 80 K temperature shifts in the blue and red wavelength region respectively (Zhang JJ et al 2013;Zhao Y et al 2017). Finally, to test compound effects, a similar analysis has been performed by simultaneously shifting two system function parameters.…”

Section: Robustness Of Optimal System Functions Under Small Parameter Shiftsmentioning

confidence: 99%

Improved and Robust Spectral Reflectance Estimation

Zhang

Meuret

Xiang-guo

et al. 2020

LEUKOS

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Accurately estimating spectral reflectance functions from color camera images is a hot research subject that demonstrates tremendous potential for illuminating engineering and computer vision applications. However, the impact of the illumination spectrum and camera responsivity (system functions) to the estimation accuracy has not been systematically studied so far, nor the impact of 'training' spectral reflectance set. In this study, a dual imaging reflectance optimization system is used based on a neural network and optimal system functions that are resp. trained and optimized using several sample sets. Simulations showed that such optimal systems, trained and optimized with the IES TM30 spectral reflectance set, can have a substantially higher estimation accuracy compared to 'real' systems composed of commercially available projector spectra and camera responsivities and that they are sufficiently robust under small changes in system function peak wavelength and spectral width due to changes in working temperature or with passing time. An analysis of the impact of the specific sample set database adopted for neural net training on estimation accuracy showed that training with the IES set results in good and stable performance, even for other sample sets and different illumination spectra. Training with the spectrally uniform IES spectral reflectance set is therefore advised for general purpose, high-accuracy reflectance estimation systems. A comparison with a state-ofthe-art method shows that the proposed method has a higher color prediction accuracy and a significantly shorter running time for realistic images with high resolution.

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Section: Robustness Of Optimal System Functions Under Small Parameter Shiftsmentioning

confidence: 99%

Improved and Robust Spectral Reflectance Estimation

Zhang

Meuret

Xiang-guo

et al. 2020

LEUKOS

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“…In addition to optical properties, the thermal properties are also an important concern for WLEDs, because higher temperature leads to the quenching and degradation of QDs or KSF [29], [35]. To explore the temperature distribution of the WLEDs, we recorded the infrared thermal images of two types at 50 mA from switching to closing.…”

Section: Comparison Of Thermal Properties Between Qds-up Type and mentioning

confidence: 99%

Improvement of Optical and Thermal Properties for Quantum Dots WLEDs by Controlling Layer Location

Tang

et al. 2019

IEEE Access

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The inorganic halide perovskite quantum dots (QDs) have been considered as a promising substitute for white light-emitting diodes (WLEDs). In this paper, the green CsPbBr 3 QDs and red K 2 SiF 6 :Mn 4+ (KSF) phosphor were used to fabricate the conversion layers. Because the location of the layers is fundamental to the absorption priority of blue light, the location of KSF and QDs were controlled and the QDs-up type and QDs-down type WLEDs were made. The optical power, luminous efficiency, CCE, and luminous intensity in the middle of QDs-up type are 13.83 mW, 13.54 lm/W, 11.94%, and 2.65 cd, meaning 24.26%, 25.72%, 2.63%, and 23.83% higher than those of QDs-down type, respectively. In addition, the QDs-up type has a lower correlated color temperature (CCT) shift of 734 K and a decreased highest temperature of 56.8 • (51.5% and 14.9% lower). These key property differences indicate that the QDs-up type is more suitable for the application in display and backlight. In order to explore the reasons for these differences, the emission spectra, CCE, reflection rate, absorption rate, and temperature curves of QDs or KSF films were also analyzed, which provided a better understanding of designing package structures. INDEX TERMS Quantum dots WLEDs, optical properties, thermal properties, layer location.

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“…[1][2][3][4][5][6] Due to the extraordinary characteristics of low power consumption, being nontoxic, long lifetime and high efficiency, GaN-based materials are promising for the above fields. 7,8 Because of its tunable bandgap and superior stability against radiation, the (Al,Ga)N material has already attracted extensive consideration. 9,10 Thus, achieving flexible and transparent (Al,Ga)N films is a key step for many markets and applications, including ultraviolet (UV) photodetectors (PDs).…”

Section: Introductionmentioning

confidence: 99%