This paper aims to propose an effective approach in the fault diagnosis based on neural networks. In particular, a MultiLayer based on MultiValued Neuron artificial Neural Network (MLMVNN) with a complex QRdecomposition is used to identify parameters values changing (i.e. faults detection) on a Boost converter starting from voltages and currents in steady state measurements.
MLMVNN for parameters faults detection in a DC-DC boost converter / Baldanzi, I.; Catelani, M.; Ciani, L.; Kazimierczuk, M. K.; Luchetta, A.; Manetti, S.; Reatti, A.. - STAMPA. - (2015), pp. 1-5. (Intervento presentato al convegno 21st IMEKO World Congress on Measurement in Research and Industry tenutosi a Prague; Czech Republic nel 30 August 2015 through 4 September).
MLMVNN for parameters faults detection in a DC-DC boost converter
CATELANI, MARCANTONIO;CIANI, LORENZO;LUCHETTA, ANTONIO;MANETTI, STEFANO;REATTI, ALBERTOSupervision
2015
Abstract
This paper aims to propose an effective approach in the fault diagnosis based on neural networks. In particular, a MultiLayer based on MultiValued Neuron artificial Neural Network (MLMVNN) with a complex QRdecomposition is used to identify parameters values changing (i.e. faults detection) on a Boost converter starting from voltages and currents in steady state measurements.
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