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首页> 外文期刊>Photonics Journal, IEEE >Lumen Degradation Lifetime Prediction for High-Power White LEDs Based on the Gamma Process Model
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Lumen Degradation Lifetime Prediction for High-Power White LEDs Based on the Gamma Process Model

机译:基于伽玛过程模型的大功率白光LED流明退化寿命预测

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Nowadays, due to the advancement of design and manufacturing technology, there are many consumer products with high reliability. Similarly, the competition in the business sector influences the product development time to become shorter and that makes it difficult for manufacturers to evaluate the reliability of current products before new products are released to the market. This phenomenon is manifested in the lighting industry, especially for the high power white light-emitting diodes (LEDs) as these products have a long lifetime and high reliability. Currently, the standard to predict the lifetime of LEDs is based on a deterministic nonlinear least squares method which has low prediction accuracy. To overcome this, degradation models are being used to study the reliability of such products, considering the uncertainties and the quality characteristics whose degradation over a period of time can be related to the product lifetime. A stochastic approach based on gamma distributed degradation (GDD) is proposed in this study to estimate the long-term lumen degradation lifetime of phosphor-converted white LEDs. An accelerated thermal degradation test was designed to gather luminous flux degradation data which was analyzed based on maximum likelihood estimation (MLE) and the method of moments (MM) to estimate the parameters for the GDD model. The MLE method has shown superiority over MM in terms of the estimation of the model parameters due to its iterative algorithm being likely to find the optimal estimation. The lifetime prediction results show that the accuracy of the proposed method is much better than the TM-21 nonlinear least squares (NLS) approach which makes it promising for future industrial applications.
机译:当今,由于设计和制造技术的进步,许多消费产品具有很高的可靠性。同样,商业领域的竞争会影响产品开发时间的缩短,从而使制造商难以在新产品投放市场之前评估当前产品的可靠性。这种现象在照明行业中尤为明显,特别是对于大功率白光发光二极管(LED),因为这些产品具有长寿命和高可靠性。当前,预测LED寿命的标准是基于确定性非线性最小二乘法,该方法具有较低的预测精度。为了克服这个问题,考虑到不确定性和质量特性,使用退化模型来研究此类产品的可靠性,这些不确定性和质量特性在一段时间内的退化可能与产品寿命有关。在这项研究中,提出了一种基于伽马分布退化(GDD)的随机方法来估计磷光体转换后的白光LED的长期流明退化寿命。设计了加速热降解测试以收集光通量降解数据,该数据基于最大似然估计(MLE)和矩量法(MM)进行了分析,以估计GDD模型的参数。在模型参数的估计方面,MLE方法已显示出优于MM的优势,这是因为其迭代算法很可能找到最佳估计。寿命预测结果表明,该方法的精度比TM-21非线性最小二乘法(NLS)方法要好得多,这使其在未来的工业应用中很有希望。

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