Title

Torsional vibration identification using electrical signatures analysis in induction machine-based systems

Document Type

Conference Proceeding

Publication Date

1-22-2019

Publication Title

Midwest Symposium on Circuits and Systems

Volume

2018-August

First Page

813

Keywords

Fault diagnosis, Gears, Induction motors, Monitoring, Real-time systems, Signal processing, Torsional vibration

Last Page

816

Abstract

This paper deals with a general approach to the feasibility study of the torsional vibration recognition through electrical signatures analysis in induction machine-based systems. The prior works on this specific topic have shown that in case of gear tooth localized fault, the amplitude of main torsional resonance frequency of the electromechanical system was amplified in the stator current space vector instantaneous frequency. Following this initial successful attempt, this work is conducted to establish a common procedure which defines the response of electrical signatures to the torsional vibrations induced by a fault located on the mechanical drive train. The most sensitive electrical signature can be considered for feature extraction and non-invasive torsional vibration analysis accordingly. An experimental setup based on a 250W three-phase squirrel-cage induction machine shaft-connected to a single-stage spur gear is utilized for validation of the proposed approach.

DOI

10.1109/MWSCAS.2018.8623846

ISSN

15483746

ISBN

9781538673928

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