@proceedings {4519,
	title = {Bayesian Framework Approach for Prognostic Studies in Electrolytic Capacitor under Thermal Overstress Conditions},
	journal = {Annual Conference of the Prognostics and Health Management Society},
	year = {2012},
	month = {09/2012},
	publisher = {PHM Society},
	address = {Minneapolis, MN},
	abstract = {Electrolytic capacitors are used in several applications ranging from power supplies for safety critical  avionics equipment to power drivers for electro-mechanical actuators. Past experiences show that capacitors tend to degrade and fail faster under high electrical and thermal stress conditions that they are often subjected to during operations. This makes them good candidates for prognostics and health management. Model based prognostics captures system knowledge in the form of physics-based models of components in order to obtain accurate predictions of end of life based on their current state of health and their anticipated future use and operational conditions. The focus of this paper is on deriving first principles degradation models for thermal stress conditions and implementing Bayesian framework for making remaining useful life predictions. Data collected from simultaneous experiments are used to  validate the models. Our overall goal is to derive accurate models of capacitor degradation, and use them to remaining useful life in DC-DC converters.},
	isbn = {978-1-936263-05-9},
	author = {Kulkarni, Chetan and Celaya Jose and Biswas, Gautam and Goebel Kai}
}
