DocumentCode :
1841164
Title :
Application of Kalman filters in model-based fault diagnosis of a DC-DC boost converter
Author :
Izadian, Afshin ; Khayyer, Pardis
Author_Institution :
Res. Member of Energy Center, Purdue Univ., West Lafayette, IN, USA
fYear :
2010
fDate :
7-10 Nov. 2010
Firstpage :
369
Lastpage :
372
Abstract :
This paper illustrates how Kalman filters were used in a model-based fault diagnosis of a DC-DC boost converter. A time-averaging model was used with the Kalman filters to generate residual signals. Multiple signature faults were developed in fault scenarios to identify critical variations in the elements of a power converter using the adaptive estimation technique. Results show a very precise and accurate fault diagnosis of signature faults. The fault diagnosis shows a high performance in transients and against noise in the circuit.
Keywords :
DC-DC power convertors; Kalman filters; adaptive estimation; fault diagnosis; DC-DC boost converter; Kalman filters; adaptive estimation; fault diagnosis; signature faults; time-averaging model; Circuit faults; Converters; Fault diagnosis; Integrated circuit modeling; Kalman filters; Noise;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
IECON 2010 - 36th Annual Conference on IEEE Industrial Electronics Society
Conference_Location :
Glendale, AZ
ISSN :
1553-572X
Print_ISBN :
978-1-4244-5225-5
Electronic_ISBN :
1553-572X
Type :
conf
DOI :
10.1109/IECON.2010.5674998
Filename :
5674998
Link To Document :
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