Accelerated Aging Experiments for Capacitor Health Monitoring and Prognostics

Metadata Updated: November 12, 2020

This paper discusses experimental setups for health monitoring and prognostics of electrolytic capacitors under nominal operation and accelerated aging conditions. Electrolytic capacitors have higher failure rates than other components in electronic systems like power drives, power converters etc. Our current work focuses on developing first-principles-based degradation models for electrolytic capacitors under varying electrical and thermal stress conditions. Prognostics and health management for electronic systems aims to predict the onset of faults, study causes for system degradation, and accurately compute remaining useful life. Accelerated life test methods are often used in prognostics research as a way to model multiple causes and assess the effects of the degradation process through time. It also allows for the identification and study of different failure mechanisms and their relationships under different operating conditions. Experiments are designed for aging of the capacitors such that the degradation pattern induced by the aging can be monitored and analyzed. Experimental setups and data collection methods are presented to demonstrate this approach.

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Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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Metadata Created Date November 12, 2020
Metadata Updated Date November 12, 2020
Data Update Frequency irregular

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Harvested from NASA Data.json

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Resource Type Dataset
Metadata Created Date November 12, 2020
Metadata Updated Date November 12, 2020
Publisher Dashlink
Unique Identifier Unknown
Maintainer
Identifier DASHLINK_695
Data First Published 2013-04-12
Data Last Modified 2020-01-29
Public Access Level public
Data Update Frequency irregular
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Harvest Source Title NASA Data.json
Homepage URL https://c3.nasa.gov/dashlink/resources/695/
Program Code 026:029
Source Datajson Identifier True
Source Hash 46fe99539fc447eef3d349907b64537f5450cc1f
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