Use of optical fibres for multi-parameter monitoring in electrical AC machines

Hind, David Martin and Gerada, C. and Galea, Michael and Borg Bartalo, James and Fabian, Matthias and Sun, Tong and Grattan, Kenneth T.V. (2017) Use of optical fibres for multi-parameter monitoring in electrical AC machines. In: IEEE 11th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED 2017), 29 Aug - 1 Sept 2017, Tinos, Greece.

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Abstract

This paper describes a new approach to multi-parameter monitoring for electrical AC machines. It is demonstrated that speed, torque and temperature can be measured using optical fibres incorporating sensors in the form of fibre Bragg gratings (FBGs) distributed around the machine. One fibre can incorporate several FBGs and hence provide several measurements. Experimental results showing speed, torque, direction of rotation, stator housing vibration and temperature measured using the FBG method are presented and validated against measurements obtained from conventional sensors. The results show that the optical fibre based approach allows multiple parameters to be monitored accurately and simultaneously with only a fraction of the usual monitoring equipment required. Another advantage of the proposed method is the EMI immunity naturally provided by optical solutions. The presented measurement technique can also offer a new alternative approach to sensorless control.

Item Type: Conference or Workshop Item (Paper)
Additional Information: © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Appears in conference proceedings with ISBN 9781509004096
Keywords: Optical fibre; Fibre Bragg grating (FBG); Multi parameter monitoring; Health monitoring; Sensorless
Schools/Departments: University of Nottingham, UK > Faculty of Engineering > Department of Electrical and Electronic Engineering
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Depositing User: Burns, Rebecca
Date Deposited: 17 Nov 2017 13:02
Last Modified: 18 Nov 2017 02:15
URI: http://eprints.nottingham.ac.uk/id/eprint/48155

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