Wyniki wyszukiwania - Biblioteka Nauki

1

Wind turbines' rolling element bearings fault detection enhancement using minimum entropy deconvolution

100%

Barszcz T. , Sawalhi N.

Diagnostyka

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2011

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tom nr 3(59)

53-59

EN

Minimum Entropy Deconvolution (MED) has been recently introduced to the machine condition monitoring field to enhance fault detection in rolling element bearings and gears. MED proved to be an excellent aid to the extraction of these impulses and diagnosing their origin, i.e. the defective component of the bearing. In this paper, MED was applied for fault detection and diagnosis in rolling element bearings in wind turbines. MED parameter selection as well as its combination with pre-whitening is discussed. Two main cases are presented to illustrate the benefits of the MED technique. The first was taken from a fan bladed test rig. The second case was taken from a wind turbine with an inner race fault. The usage of the MED technique has shown a strong enhancement for both fault detection and diagnosis. The paper contributes to the knowledge of fault detection of rolling elements bearings through providing an insight into the usage of MED in rolling element bearings diagnostic by providing a guide for the user to select optimum parameters for the MED filter and illustrating these on new interesting cases both from a lab environment and an actual case.

PL

Metoda Minimum Etropy Deconvolution (MED) została niedawno wprowadzona do diagnostyki w celu poprawy wykrywania uszkodzeń łożysk tocznych i przekładni. MED okazała się bardzo pomocna w ekstrakcji impulsów pochodzących od tych uszkodzeń i określania miejsca ich pochodzenia (np. uszkodzonego elementu łożyska). W niniejszym artykule MED zastosowano do wykrywania uszkodzeń łożysk tocznych w turbinach wiatrowych. W artykule opisano zagadnienie selekcji parametrów metody MED oraz metody "wybielania sygnału" (ang. pre-whitening). Korzyści płynące z zastosowania metody przedstawiono na dwóch przypadkach. Pierwszym jest stanowisko laboratoryjne, a drugim - turbina wiatrowa z uszkodzoną bieżnią wewnętrzną łożyska generatora. Zastosowanie metody MED pozwoliło na znaczącą poprawę zarówno wykrycia, jak i lokalizacji uszkodzenia. Najistotniejszymi częściami niniejszego artykułu są: opis metody MED, wskazówki dotyczące optymalnego dostrojenia metody oraz interesujące przypadki zarówno laboratoryjne, jak i rzeczywiste.

2

Fault Detection Enhancement in Rolling Element Bearings Using the Minimum Entropy Deconvolution

100%

Barszcz T. , Sawalhi N.

Archives of Acoustics

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2012

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tom Vol. 37, No. 2

131-141

EN

Minimum Entropy Deconvolution (MED) has been recently introduced to the machine condition mon- itoring field to enhance fault detection in rolling element bearings and gears. MED proved to be an excellent aid to the extraction of these impulses and diagnosing their origin, i.e. the defective component of the bearing. In this paper, MED is revisited and re-introduced with further insights into its application to fault detection and diagnosis in rolling element bearings. The MED parameter selection as well as its combination with pre-whitening is discussed. Two main cases are presented to illustrate the benefits of the MED technique. The first one was taken from a fan bladed test rig. The second case was taken from a wind turbine with an inner race fault. The usage of the MED technique has shown a strong enhancement for both fault detection and diagnosis. The paper contributes to the knowledge of fault detection of rolling element bearings through providing an insight into the usage of MED in rolling element bearings diag- nostic. This provides a guide for the user to select optimum parameters for the MED filter and illustrates these on new interesting cases both from a lab environment and an actual case.

3

Comparison of amplitude-based and phase-based method for speed tracking in application to wind turbines

80%

Urbanek J. , Barszcz T. , Sawalhi N. , Randall R. B.

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tom Vol. 18, nr 2

295-303

EN

Focus of the vibration expert community shifts more and more towards diagnosing machines subjected to varying rotational speeds and loads. Such machines require order analysis for proper fault detection and identification. In many cases phase markers (tachometers, encoders, etc) are used to help performing the resampling of the vibration signals to remove the speed fluctuations and smearing from the spectrum (order tracking). However, not all machines have the facility to install speed tracking sensors, due to design or cost reasons, and the signal itself has to then be used to extract this information. This paper is focused on the problem of speed tracking in wind turbines, which represent typical situations for speed and load variation. The basic design of a wind turbine is presented. Two main types of speed control i.e. stall and pitch control are presented. The authors have investigated two methods of speed tracking, using information from the signal (without relying on a speed signal). One method is based on extracting a reference signal to use as a tachometer, while the other is phase-based (phase demodulation).Both methods are presented and applied to the vibration data from real wind turbines. The results are compared with each other and with the actual speed data.