Видання НТУ "ХПІ"
Постійне посилання на розділhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/62886
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Документ Application of a wavelet neural network approach to detect stator winding short circuits in asynchronous machines(Національний технічний університет "Харківський політехнічний інститут", 2023) Sakhara, S.; Brahimi, M.; Nacib, L.; Layadi, T. M.Nowadays, fault diagnosis of induction machines plays an important role in industrial fields. In this paper, Artificial Neural Network (ANN) model has been proposed for automatic fault diagnosis of an induction machine. The aim of this research study is to design a neural network model that allows generating a large database. This database can cover maximum possible of the stator faults. The fault considered in this study take into account a short circuit with large variations in the machine load. Moreover, the objective is to automate the diagnosis algorithm by using ANN classifier. Method. The database used for the ANN is based on indicators which are obtained from wavelet analysis of the machine stator current of one phase. The developed neural model allows to taking in consideration imbalances which are generated by short circuits in the machine stator. The implemented mathematical model in the expert system is based on a three-phase model. The mathematical parameters considered in this model are calculated online. The characteristic vector of the ANN model is formed by decomposition of stator current signal using wavelet discrete technique. Obtained results show that this technique allows to ensure more detection with clear evaluation of turn number in short circuit. Also, the developed expert system for the taken configurations is characterized by high precision.Документ Impact of fractional filter in PI control loop applied to induction motor speed drive(Національний технічний університет "Харківський політехнічний інститут", 2022) Hassainia, Saida ; Ladaci, Samir; Kechida, Sihem; Khelil, KhaledOne of the main problems of electrical machine control systems is to obtain a satisfactory performance in the rejection of load disturbances, as well as in the set-point tracking tasks. Generally, the development of control algorithms does not take into account the presence of noise. Appropriate filtering is, therefore, essential to reduce the impact of noise on the output of the controller, in addition to the machine output. Recently, there has been a great tendency toward using fractional calculus to solve engineering problems. The filtering is one of the fields in which fractional calculus has received great attention. The importance of filters in signal processing and other engineering areas is unquestionable Novelty. The proposed work is intended to be a contribution in the recent works conducted on the influence of the fractional filtering on the control robustness of induction machines control. Purpose. The main contribution of this research is the application of fractional filtering to the standard PI control loop for an induction motor speed drive. Methods. In order to assess its impact and benefit, different structures for introducing the filters are investigated, A first order filter is considered in different positions, whether before or after the controller or even in both positions at the same time, with a noise source. A review of the index performance evolution (the Integral Square Error, Integral Absolute Error and Integral Time Absolute Error) has allowed a configuration design of the filter. Results. Intensive simulations were performed with a control setup using integer and fractional order filters, which permitted to conclude that the fractional filters give better performance indices compared to the integer one and thus improve the dynamic characteristics of the system.