Software Sensors for Order Tracking Applied to Permanent Magnet Synchronous Generator Diagnostics: A Comparative Study

The paper deals with software sensors which facilitates the diagnosis of electrical machines in non-stationary operating conditions. The technique targeted is order tracking for which different techniques exist to estimate the speed and angle of rotation. However, from a methodological point of view...

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Main Authors: Laurent Rambault, Abdallah Allouche, Erik Etien, Anas Sakout, Thierry Doget, Sebastien Cauet
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Robotics
Subjects:
Online Access:https://www.mdpi.com/2218-6581/10/2/59
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author Laurent Rambault
Abdallah Allouche
Erik Etien
Anas Sakout
Thierry Doget
Sebastien Cauet
author_facet Laurent Rambault
Abdallah Allouche
Erik Etien
Anas Sakout
Thierry Doget
Sebastien Cauet
author_sort Laurent Rambault
collection DOAJ
description The paper deals with software sensors which facilitates the diagnosis of electrical machines in non-stationary operating conditions. The technique targeted is order tracking for which different techniques exist to estimate the speed and angle of rotation. However, from a methodological point of view, this paper offers a comparison of several methods in order to evaluate their performance from tests on a test bench. In addition, to perform the tests, it is necessary to initialize the different methods to make them work correctly. In particular, an identification technique is proposed as well as a way to facilitate initialization. The example of this paper is that of a synchronous generator. Angular sampling allows the spectrum to be stationary and the interpretation of a possible defect. The realization of the angular sampling and the first diagnostic elements require the knowledge of two fundamental quantities: the speed of rotation and the angular position of the shaft. The estimation of the rotation speed as well as the estimation of the angular position of the shaft are carried out from the measurement of an electric current (or three electric currents and three voltages). Four methods are proposed and evaluated to realize software sensors: identification technique, PLL (Phase Locked Loop), Concordia transform and an observer. The four methods are evaluated on measurements carried out on a test bench. The results are discussed from the diagnosis of a mechanical fault.
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spelling doaj.art-2e9f4edbb44243dfac0704b719d685e72023-11-21T14:46:07ZengMDPI AGRobotics2218-65812021-04-011025910.3390/robotics10020059Software Sensors for Order Tracking Applied to Permanent Magnet Synchronous Generator Diagnostics: A Comparative StudyLaurent Rambault0Abdallah Allouche1Erik Etien2Anas Sakout3Thierry Doget4Sebastien Cauet5Laboratoire d’Informatique et Automatique des Systemes, University of Poitiers, 86073 Poitiers, FranceLaboratoire d’Informatique et Automatique des Systemes, University of Poitiers, 86073 Poitiers, FranceLaboratoire d’Informatique et Automatique des Systemes, University of Poitiers, 86073 Poitiers, FranceLaSIE Laboratory UMR CNRS 7356, University of la Rochelle, 17042 La Rochelle, FranceLaboratoire d’Informatique et Automatique des Systemes, University of Poitiers, 86073 Poitiers, FranceLaboratoire d’Informatique et Automatique des Systemes, University of Poitiers, 86073 Poitiers, FranceThe paper deals with software sensors which facilitates the diagnosis of electrical machines in non-stationary operating conditions. The technique targeted is order tracking for which different techniques exist to estimate the speed and angle of rotation. However, from a methodological point of view, this paper offers a comparison of several methods in order to evaluate their performance from tests on a test bench. In addition, to perform the tests, it is necessary to initialize the different methods to make them work correctly. In particular, an identification technique is proposed as well as a way to facilitate initialization. The example of this paper is that of a synchronous generator. Angular sampling allows the spectrum to be stationary and the interpretation of a possible defect. The realization of the angular sampling and the first diagnostic elements require the knowledge of two fundamental quantities: the speed of rotation and the angular position of the shaft. The estimation of the rotation speed as well as the estimation of the angular position of the shaft are carried out from the measurement of an electric current (or three electric currents and three voltages). Four methods are proposed and evaluated to realize software sensors: identification technique, PLL (Phase Locked Loop), Concordia transform and an observer. The four methods are evaluated on measurements carried out on a test bench. The results are discussed from the diagnosis of a mechanical fault.https://www.mdpi.com/2218-6581/10/2/59software sensorsfrequency trackingnon stationaryangular samplingsynchronous machine
spellingShingle Laurent Rambault
Abdallah Allouche
Erik Etien
Anas Sakout
Thierry Doget
Sebastien Cauet
Software Sensors for Order Tracking Applied to Permanent Magnet Synchronous Generator Diagnostics: A Comparative Study
Robotics
software sensors
frequency tracking
non stationary
angular sampling
synchronous machine
title Software Sensors for Order Tracking Applied to Permanent Magnet Synchronous Generator Diagnostics: A Comparative Study
title_full Software Sensors for Order Tracking Applied to Permanent Magnet Synchronous Generator Diagnostics: A Comparative Study
title_fullStr Software Sensors for Order Tracking Applied to Permanent Magnet Synchronous Generator Diagnostics: A Comparative Study
title_full_unstemmed Software Sensors for Order Tracking Applied to Permanent Magnet Synchronous Generator Diagnostics: A Comparative Study
title_short Software Sensors for Order Tracking Applied to Permanent Magnet Synchronous Generator Diagnostics: A Comparative Study
title_sort software sensors for order tracking applied to permanent magnet synchronous generator diagnostics a comparative study
topic software sensors
frequency tracking
non stationary
angular sampling
synchronous machine
url https://www.mdpi.com/2218-6581/10/2/59
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