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

Abstract : 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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https://hal-univ-rochelle.archives-ouvertes.fr/hal-03201810
Contributor : Anas Sakout <>
Submitted on : Monday, April 19, 2021 - 12:26:38 PM
Last modification on : Tuesday, April 20, 2021 - 3:32:33 AM

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Laurent Rambault, Abdallah Allouche, Erik Etien, Anas Sakout, Thierry Doget, et al.. Software Sensors for Order Tracking Applied to Permanent Magnet Synchronous Generator Diagnostics: A Comparative Study. Robotics, Elsevier, 2021, 10 (2), pp.59. ⟨10.3390/robotics10020059⟩. ⟨hal-03201810⟩

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