Reliability Model of LEDs Based on Artificial Neural Network

HUANG Wei-ming; WEN Shang-sheng; XIA Yun-yun

doi:10.3788/fgxb20153608.0962

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Reliability Model of LEDs Based on Artificial Neural Network

更新时间：2020-08-12

- Reliability Model of LEDs Based on Artificial Neural Network
- Chinese Journal of Luminescence Vol. 36, Issue 8, Pages: 962-968(2015)
- 作者机构：
  
  发光材料与器件国家重点实验室华南理工大学,广东广州,510640
- 作者简介：
- 基金信息：
- DOI：10.3788/fgxb20153608.0962
  CLC： TN312+.8
- Received：27 April 2015，
  
  Revised：26 June 2015，
  
  Published：03 August 2015
- 稿件说明：
移动端阅览
黄伟明, 文尚胜, 夏云云. 基于BP神经网络的LED可靠性模型研究[J]. 发光学报, 2015,36(8): 962-968

HUANG Wei-ming, WEN Shang-sheng, XIA Yun-yun. Reliability Model of LEDs Based on Artificial Neural Network[J]. Chinese Journal of Luminescence, 2015,36(8): 962-968
黄伟明, 文尚胜, 夏云云. 基于BP神经网络的LED可靠性模型研究[J]. 发光学报, 2015,36(8): 962-968 DOI： 10.3788/fgxb20153608.0962.

HUANG Wei-ming, WEN Shang-sheng, XIA Yun-yun. Reliability Model of LEDs Based on Artificial Neural Network[J]. Chinese Journal of Luminescence, 2015,36(8): 962-968 DOI： 10.3788/fgxb20153608.0962.

摘要

根据LED可靠性与相关参数的映射关系

建立拓扑结构为6-12-1的BP神经网络.以实测白光LED芯片的理想因子、结温、色温漂移等参数为输入量

以寿命为输出量

计算模型精度.研究结果表明

该模型有良好的外推能力及鲁棒性

可在短时间内成功预测LED寿命

神经网络训练结果相关系数为99.8%

检验组误差小于3%.

Abstract

We proposed the 6-12-1 topology BP neural network according to the LED reliability and relevant element. The ideal factor

junction temperature

color temperature drift of the white LED chip and so on were measured as the input and the life as output to calculate the precision of the model. The model shows a good ability of extrapolation and robustness

and can predict the life of the LED in a short time. The linear correlation of ANN reaches 99.8%

and the inspection group error is less than 3%.

关键词

Keywords

references

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