DocumentCode :
235594
Title :
Life prediction and classification of failure modes in solid state luminaires using Bayesian Probabilistic Models
Author :
Lall, P. ; Junchao Wei ; Sakalaukus, Peter
Author_Institution :
Dept. of Mech. Eng., Auburn Univ., Auburn, AL, USA
fYear :
2014
fDate :
27-30 May 2014
Firstpage :
2053
Lastpage :
2062
Abstract :
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.
Keywords :
Bayes methods; LED lamps; failure analysis; Bayesian probabilistic models; Philips LED lamps; correlated color temperature data; failure mechanisms; failure mode classification; life prediction; lumen degradation; luminous flux output; solid state luminaires; temperature 85 C; Bayes methods; Degradation; Image color analysis; LED lamps; Maintenance engineering; Solids;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronic Components and Technology Conference (ECTC), 2014 IEEE 64th
Conference_Location :
Orlando, FL
Type :
conf
DOI :
10.1109/ECTC.2014.6897585
Filename :
6897585
Link To Document :
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