The importance of testability analysis in neural network based fault diagnosis of DC-DC converters is discussed in this paper. Theoretical fundamentals and an applicative example are presented, by taking into account the single-fault hypothesis. A program for testability analysis of switched DC-DC converters is used in the example. It relies on symbolic analysis techniques, which may be used to simulate switched circuits in a very easy and fast way.
Testability Analysis in Neural Network Based Fault Diagnosis of DC-DC Converter / Aizenberg I.; Bindi M.; Grasso F.; Luchetta A.; Manetti S.; Piccirilli M.C.. - ELETTRONICO. - (2019), pp. 265-268. (Intervento presentato al convegno 5th International Forum on Research and Technologies for Society and Industry, RTSI 2019 tenutosi a FIRENZE nel 2019) [10.1109/RTSI.2019.8895583].
Testability Analysis in Neural Network Based Fault Diagnosis of DC-DC Converter
Aizenberg I.Conceptualization
;Bindi M.Writing – Original Draft Preparation
;Grasso F.Validation
;Luchetta A.
Writing – Original Draft Preparation
;Manetti S.Investigation
;Piccirilli M. C.Writing – Review & Editing
2019
Abstract
The importance of testability analysis in neural network based fault diagnosis of DC-DC converters is discussed in this paper. Theoretical fundamentals and an applicative example are presented, by taking into account the single-fault hypothesis. A program for testability analysis of switched DC-DC converters is used in the example. It relies on symbolic analysis techniques, which may be used to simulate switched circuits in a very easy and fast way.
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