固态灯寿命预测与故障模式分类的贝叶斯模型

P. Lall, Junchao Wei, P. Sakalaukus
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引用次数: 8

摘要

已经开发了一种新的方法来评估固态灯具退化的开始,通过使用目前用于识别故障的流明退化之外的指标来对故障机制进行分类。在85°C/85%RH条件下,飞利浦LED灯的光通量输出、相关色温数据已被收集,直到灯失效。所获得的数据与贝叶斯概率模型结合使用,通过识别特征空间中具有累积损伤的灯具和超过故障阈值的灯具之间的决策边界,来识别在故障发生之前就开始退化的灯具。此外,具有不同失效模式的灯具已与健康的原始灯具分开分类。预计,新的测试技术将允许开发失效分布,而无需测试直到L70寿命的失效表现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bayesian models for life prediction and fault-mode classification in solid state lamps
A new method has been developed for assessment of the onset of degradation in solid state luminaires to classify failure mechanisms by using metrics beyond lumen degradation that are currently used for identification of failure. Luminous Flux output, Correlated Color Temperature Data on Philips LED Lamps has been gathered under 85°C/85%RH till lamp failure. The acquired data has been used in conjunction with Bayesian Probabilistic Models to identify luminaires with onset of degradation much prior to failure through identification of decision boundaries between lamps with accrued damage and lamps beyond the failure threshold in the feature space. In addition luminaires with different failure modes have been classified separately from healthy pristine luminaires. It is expected that, the new test technique will allow the development of failure distributions without testing till L70 life for the manifestation of failure.
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