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Fault-Mode Classification of Solid State Luminaires Using Bayesian Probabilistic Models

[+] Author Affiliations
Pradeep Lall, Junchao Wei, Peter Sakalaukus

Auburn University, Auburn, AL

Paper No. IMECE2014-39523, pp. V010T13A079; 12 pages
doi:10.1115/IMECE2014-39523
From:
  • ASME 2014 International Mechanical Engineering Congress and Exposition
  • Volume 10: Micro- and Nano-Systems Engineering and Packaging
  • Montreal, Quebec, Canada, November 14–20, 2014
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-4959-0
  • Copyright © 2014 by ASME

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.

Copyright © 2014 by ASME

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