MLMVNN FOR PARAMETERS FAULTS DETECTION IN A DC-DC BOOST CONVERTER

I. Baldanzi, M. Catelani , L. Ciani , M. K. Kazimierczuk , A. Luchetta , S. Manetti , A. Reatti
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 QR-decomposition is used to identify parameters values changing (i.e. faults detection) on a Boost converter starting from voltages and currents in steady state measurements.
Keywords:
neural networks, boost converter, faults detection, diagnostics
Download:
IMEKO-WC-2015-TC10-232.pdf
DOI:
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Event details
Event name:
XXI IMEKO World Congress
Title:

Measurement in Research and Industry

Place:
Prague, CZECH REPUBLIC
Time:
30 August 2015 - 04 September 2015