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Experimental investigation on induction motors inter-turns short-circuit and broken rotor bars faults diagnosis through the discrete wavelet transform

Experimentelle Untersuchung von Windungsschlüssen und Stabbrüchen an Asynchronmaschinen mittels diskreter Wavelet-Transformation

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Abstract

This paper deals with the problem of fault detection in induction motors using the discrete wavelet transform (DWT) method. The DWT is a mathematical method used to extract different frequency components from a given signal. It is based on the decomposition of the processed signals into wavelet approximation and detail coefficients. In order to detect inter-turns short-circuit (ITSC) and broken rotor bars (BRBs) faults, the DWT is applied on two different signals: the current envelope and the current Park’s vector modulus. This study is performed using experimental tests carried-out on a 3 kW squirrel cage induction motor. The energy evaluation of known bandwidth details allows defining a fault severity factor (FSF). This FSF is used to show which signals, wavelet type and wavelet order are more sensitive for the fault detection task.

Zusammenfassung

Diese Arbeit befasst sich mit der Fehlererkennung in Asynchronmaschinen mittels diskreter Wavelet-Transformation (DWT). Die DWT ist eine mathematische Methode, um verschiedene Frequenzkomponenten aus einem gegebenen Signal zu extrahieren. Sie basiert auf der Zerlegung des verarbeiteten Signals in Tieffrequenzanteile und Hochfrequenzanteile. Um Windungsschlüsse und Rotorstabbrüche zu erkennen, wird die DWT auf zwei unterschiedliche Signale angewendet: die Hüllkurve des Stroms und den Betrag des Stromvektors nach der Park-Transformation. Die Untersuchungen wurden basierend auf Messungen an einer 3-kW-Asynchronmaschine mit Kurzschlussläufer durchgeführt. Die Auswertung der Leistungsanteile über den Frequenzbereich erlaubt die Definition eines Fehlerlevel-Faktors. Dieser Faktor kann verwendet werden, um für die Fehlererkennung geeignete Signale, Wavelet-Typen und Wavelet-Ordnungszahlen zu ermitteln.

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Authors and Affiliations

  1. Laboratoire de Modélisation des Systèmes Energétiques, LMSE, Université Mohamed Khider de Biskra, B.P. 145, R.P., 07000, Biskra, Algérie

    Fateh Benchabane & Abderezak Guettaf

  2. Laboratoire de Génie Energétique et Matériaux, LGEM, Université Mohamed Khider de Biskra, B.P. 145, R.P., 07000, Biskra, Algérie

    Khaled Yahia

  3. Laboratoire de Génie Electrique de Biskra, LGEB, Université Mohamed Khider de Biskra, B.P. 145, R.P., 07000, Biskra, Algérie

    Mohamed Sahraoui

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  1. Fateh Benchabane
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  2. Abderezak Guettaf
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  3. Khaled Yahia
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Correspondence to Fateh Benchabane.

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Benchabane, F., Guettaf, A., Yahia, K. et al. Experimental investigation on induction motors inter-turns short-circuit and broken rotor bars faults diagnosis through the discrete wavelet transform. Elektrotech. Inftech. 135, 187–194 (2018). https://doi.org/10.1007/s00502-018-0607-6

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  • DOI: https://doi.org/10.1007/s00502-018-0607-6

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