Induction motor windings faults detection using flux-error based mras estimators

Bednarz, Szymon Antoni; Dybkowski, Mateusz

doi:10.29354/diag/109092

Artykuł - szczegóły

Tytuł artykułu

Induction motor windings faults detection using flux-error based mras estimators

Autorzy

Bednarz Szymon Antoni , Dybkowski Mateusz

Treść / Zawartość

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DOI

10.29354/diag/109092

Warianty tytułu

Detekcja uszkodzeń uzwojeń silnika induckycjnego z zastosowaniem estymatorów mras bazujących na błędzie estymacji strumienia

Języki publikacji

Abstrakty

The paper is concerned with detection of a stator and rotor winding faults in a squirrel-cage induction motor. The idea of the fault detection is based on a hypothesis that each of windings faults results in a sharp increase or decrease of internal parameters’ values of the machine, therefore it can be treated as a suitable fault symptom. Resistances of the stator and rotor windings seem to be adequate quantities due to their direct relationship with the machine windings. An observation and analysis of the parameters’ changes in a realtime domain enables to an incipient detection of the fault. It is evident that internal parameters of the machine can’t be measured directly during operation on the drive system thus the only way is an estimation by specialized algorithms. In the paper two estimators based on Model Reference Adaptive System (MRAS) were utilized to achieve this goal. Two simple algorithms for faults detection are proposed as well. Detailed description of fault detection systems is included in the paper. Proposed systems were tested on computer simulations performed by MATLAB/Simulink software. Then, experimental tests were carried out on the laboratory setup to confirm usefulness of proposed approaches.

Artykuł skupia się na wykrywaniu wybranych uszkodzeń uzwojeń stojana i wirnika silnika indukcyjnego klatkowego. Idea detekcji opiera się na założeniu, że każde uszkodzenie uzwojeń powoduje gwałtowną zmianę wartości wewnętrznych parametrów maszyny, co może być uznane jako miarodajny symptom uszkodzenia. Najbardziej odpowiednimi parametrami wydają się być rezystancje stojana i wirnika ze względu na bezpośrednie powiązanie z uzwojeniami silnika. Obserwacja i analiza zmian wartości tych parametrów w czasie rzeczywistym umożliwia wykrycie uszkodzenia w jego wczesnym stadium. W trakcie pracy napędu nie ma możliwości pomiaru rezystancji uzwojeń, dlatego też jedynym sposobem na uzyskanie informacji o ich aktualnych wartościach jest estymacja z zastosowaniem wyspecjalizowanych algorytmów. W pracy do realizacji tego celu zastosowano układy adaptacyjne z modelem odniesienia (MRAS). Ponadto zaproponowano również dwa proste algorytmy detekcji uszkodzeń uzwojeń stojana i wirnika. W artykule przedstawiono przegląd literatury dotyczący wykrywania uszkodzeń silnika indukcyjnego z zastosowaniem estymatorów parametrów. Proponowane rozwiązanie zostało sprawdzone poprzez analizę symulacyjną przeprowadzoną w środowisku MATLAB/Simulink a także zweryfikowane na stanowisku eksperymentalnym.

Słowa kluczowe

induction motor stator faults rotor fault faults detection parameter estimator MRAS

silnik indukcyjny uszkodzenie stojana uszkodzenie wirnika wykrywanie uszkodzeń estymator parametrów MRAS

Wydawca

Polskie Towarzystwo Diagnostyki Technicznej

Czasopismo

Diagnostyka

Rocznik

2019

Tom

Vol. 20, No. 2

Strony

87--96

Opis fizyczny

Bibliogr. 44 poz., rys., tab.

Twórcy

autor

Bednarz Szymon Antoni

szymon.bednarz@pwr.edu.pl

Wrocław University of Science and Technology, Department of Electrical Machines, Drives and Measurements, Smoluchowskiego 19, 50-370, Wrocław, Poland

autor

Dybkowski Mateusz

mateusz.dybkowski@pwr.edu.pl

Wrocław University of Science and Technology, Department of Electrical Machines, Drives and Measurements, Smoluchowskiego 19, 50-370, Wrocław, Poland

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).

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Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-607b3331-5dd2-4567-a3a8-820fea188f35