Prognostics of radiation power degradation lifetime for ultraviolet light-emitting diodes using stochastic data-driven models  

作　　者：Jiajie Fan Zhou Jing Yixing Cao Mesfin Seid Ibrahim Min Li Xuejun Fan Guoqi Zhang 

机构地区：[1]Institute of Future Lighting,Academy for Engineering&Technology,Fudan University,Shanghai 200433,China [2]Shanghai Research Center for Silicon Carbide Power Devices Engineering&Technology,Fudan University,Shanghai 200433,China [3]College of Mechanical and Electrical Engineering,Hohai University,Changzhou 213022,China [4]EEMCS Faculty,Delft University of Technology,Delft 2628,the Netherlands [5]Changzhou Institute of Technology Research for Solid State Lighting,Changzhou 213161,China [6]Department of Industrial and System Engineering,The Hong Kong Polytechnic University,Hung Hom,Hong Kong [7]Department of Mechanical Engineering,Lamar University,Beaumont,TX 77710,USA

出　　处：《Energy and AI》2021年第2期91-100,共10页能源与人工智能（英文）

基　　金：The work described in this paper was partially supported by the National Natural Science Foundation of China(51805147);Shang-hai Science and Technology Development Funds(19DZ2253400);the Six Talent Peaks Project in Jiangsu Province(GDZB-017);the Fundamental Research Funds for the Central Universities(B200203031).

摘　　要：With their advantages of high efficiency,long lifetime,compact size and being free of mercury,ultraviolet light-emitting diodes(UV LEDs)are widely applied in disinfection and purification,photolithography,curing and biomedical devices.However,it is challenging to assess the reliability of UV LEDs based on the traditional life test or even the accelerated life test.In this paper,radiation power degradation modeling is proposed to estimate the lifetime of UV LEDs under both constant stress and step stress degradation tests.Stochastic data-driven predic-tions with both Gamma process and Wiener process methods are implemented,and the degradation mechanisms occurring under different aging conditions are also analyzed.The results show that,compared to least squares regression in the IESNA TM-21 industry standard recommended by the Illuminating Engineering Society of North America(IESNA),the proposed stochastic data-driven methods can predict the lifetime with high accuracy and narrow confidence intervals,which confirms that they provide more reliable information than the IESNA TM-21 standard with greater robustness.

关 键 词：Ultraviolet light-emitting diodes(UV LEDs) Degradation modeling Gamma process Wiener process IESNA TM-21 

分 类 号：TN3[电子电信—物理电子学]