Wyniki wyszukiwania - Biblioteka Nauki

1

DWT-PSD extraction feature for defect diagnosis of small wind generator

100%

Noureddine L. , Noureddine M. , Hafaifa A. , Kouzou A.

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tom Vol. 20, No. 3

45--52

EN

In this paper, the ability to detect broken rotor bar (BRB) defects in a small renewable energy system (based on a squirrel cage induction generator (SCIG)) by the digital signal processing of captured phase currents, is presented. The new approach proposed in this study is a combination of two techniques. The first technique is a discrete wavelet transform (DWT) by the decomposition of the phase current signal in multilevel frequency bands. This is performed with the analysis of some selected approximations and/or details, which contain both the lower and upper sideband components presenting the characteristic frequency of the BRB fault. The second technique is power spectral density (PSD) analysis. This approach provides the ability to optimize the diagnosis of rotor defects in electrical generators. The results obtained by the proposed DWT-PSD approach are proved and improved by comparing them with the results of the PSD analysis, obtained from the original phase current signal delivered by the 5.7-kW squirrel cage induction generator, based on a small wind energy conversion system.

2

Fault Tolerant Control Based on Extended Kalman Filter of Squirrel-Cage Induction Machines

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Khadar S. , Mekhalfia F. , Kouzou A.

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EN

Fault-tolerant control systems possess the ability of rejecting the effect of faults. They are capable of maintaining overall system stability and acceptable performance in degraded modes. Through many researches, the analysis, modeling, and simulation of various inverter and machine faults have been carried out for the purpose of providing a fault tolerance. However, most of them are based on systems redundancy principle. Among the real-time based approaches for the fault detection and diagnosis, there are several strategies such as the pseudo inverse method, the linear quadratic approach and Extended Kalman Filter based Fault Tolerant Control (EKF-FTC). In recent years the application of Kalman filter approaches has gained an increasing attention in fundamental research and application. In this paper, a FTC method dedicated to Induction Motor (IM) drive is presented. The proposed method based on an additive term to the backstepping control which based on the error of current during the appearance of fault and the adaptive gain of the Kalman filter. This method improves the performance of the backstepping control to maintain the operation despite the appearance of faults. The main objective is to ensure a minimum level of performance of the drive system that is malfunctioning.

PL

Odporne na błędy układy sterowania mają zdolność eliminacji wpływu zakłóceń. Potrafią one utrzymywać ogólną stabilność i akceptowalne działanie systemu w trybach awaryjnych. Dzięki wielu badaniom przeprowadzono analizę, modelowanie i symu- lację różnych błędów falownika i maszyny w celu zapewnienia odporności na błędy. Większość z nich wynika jednak z zasady redundancji systemów. Wśród strategii wykrywania i diagnozowania błędów w czasie rzeczywistym można wyróżnić przykładowo metodę pseudoodwrotną, metodę liniowo-kwadratową i sterowanie odporne na błędy przy użyciu rozszerzonego filtra Kalmana (EKF-FTC). W ostatnich latach metodom z użyciem filtra Kalmana poświęca się coraz więcej uwagi w podstawowych bada- niach i zastosowaniach. W niniejszym artykule przedstawiono metodę FTC zastosowaną do napędu silnika indukcyjnego (IM). Proponowana metoda polega na dodaniu do sterowania metodą całkowania wstecznego (ang. backstepping) członu addytywnego, która polega na wystąpieniu uchybu prądu w razie błędu i wzmocnienia adaptacyjnego filtra Kalmana. Metoda ta poprawia wydaj- ność sterowania za pomocą wstecznego całkowania w celu podtrzymania pracy pomimo wystąpienia błędów. Głównym celem jest zapewnienie minimalnego poziomu wydajności niesprawnego układu napędowego.

3

A robust fault diagnosis and forecasting approach based on Kalman filter and interval type-2 fuzzy logic for efficiency improvement of centrifugal gas compressor system

88%

Nail B. , Kouzou A. , Hafaifa A. , Hadroug N. , Puig V.

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tom Vol. 20, No. 2

57--75

EN

The paper proposes a robust faults detection and forecasting approach for a centrifugal gas compressor system, the mechanism of this approach used the Kalman filter to estimate and filtering the unmeasured states of the studied system based on signals data of the inputs and the outputs that have been collected experimentally on site. The intelligent faults detection expert system is designed based on the interval type-2 fuzzy logic. The present work is achieved by an important task which is the prediction of the remaining time of the system under study to reach the danger and/or the failure stage based on the Auto-regressive Integrated Moving Average (ARIMA) model, where the objective within the industrial application is to set the maintenance schedules in precisely time. The obtained results prove the performance of the proposed faults diagnosis and detection approach which can be used in several heavy industrial systems.