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

Contributo in Atti di convegno

Data di Pubblicazione:

2005

Citazione:

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.

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.

Tipologia IRIS:

03 - Contributo in volume

Keywords:

Fuzzy networks; Induction machine diagnosis; Stator faults; Virtual model validation; Virtual modeling; Wavelet analysis

Elenco autori: