This paper presents an experimental activity on Electrical Drive Diagnosis. A wavelet-based fault diagnosis algorithm previously tested in simulation is here validated experimentally. The analysis focuses on stator fault conditions and in particular on incipient faults affecting stator resistance. Together with the description of the experimental activity, a discussion on the structure of the realized board employed for data acquisition and diagnosis is also reported.

Virtual system fault models for training fuzzy-wavelet identifiers in electrical drive diagnosis : an experimental validation / L. Farronato, A. Monti, F. Ponci, A. Ferrero, L. Cristaldi, M. Lazzaroni - In: Proceedings of the IEEE instrumentation and measurement technology conference, 2005, IMTC 2005, 16-19 maggio 2005 : vol. 3 / [s.n.]. - [s.l] : IEEE (Institute of electrical and electronics engineers), 2005. - ISBN 0780388801. - pp. 2310-2315 (( Intervento presentato al 22. convegno Instrumentation and Measurement Technology Conference, 2005 tenutosi a Ottawa nel 2005.

Virtual system fault models for training fuzzy-wavelet identifiers in electrical drive diagnosis : an experimental validation

M. Lazzaroni
Ultimo
2005

Abstract

This paper presents an experimental activity on Electrical Drive Diagnosis. A wavelet-based fault diagnosis algorithm previously tested in simulation is here validated experimentally. The analysis focuses on stator fault conditions and in particular on incipient faults affecting stator resistance. Together with the description of the experimental activity, a discussion on the structure of the realized board employed for data acquisition and diagnosis is also reported.
Fuzzy networks; Induction machine diagnosis; Stator faults; Virtual model validation; Virtual modeling; Wavelet analysis
Settore ING-INF/07 - Misure Elettriche e Elettroniche
IEEE
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/12451
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