Електротехніка і Електромеханіка

Постійне посилання на розділhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/62894

Офіційний сайт http://eie.khpi.edu.ua/

Журнал публікує оригінальні результати досліджень з аналітичного, чисельного та мультифізичного методів моделювання електрофізичних процесів в електротехнічних електромеханічних та електроенергетичних установках та системах, з розробки нових електротехнічних пристроїв і систем з поліпшеними техніко-економічними та екологічними показниками в таких сферах, як: теоретична електротехніка, інженерна електрофізика, техніка сильних електричних та магнітних полів, електричні машини та апарати, електротехнічні комплекси та системи, силова електроніка, електроізоляційна та кабельна техніка, електричний транспорт, електричні станції, мережі і системи, безпека електрообладнання.

Рік заснування: 2002. Періодичність: 6 разів на рік. ISSN 2074-272X (Print), ISSN 2309-3404 (Online).

Новини

Видання включене до Переліку наукових фахових видань України з технічних наук до найвищої категорії «А» згідно Наказу МОН України №1412 від 18.12.2018 р.

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  • Ескіз
    Документ
    Artificial neural network and discrete wavelet transform for inter-turn short circuit and broken rotor bars faults diagnosis under various operating conditions
    (Національний технічний університет "Харківський політехнічний інститут", 2024) Rouaibia, Reda; Djeghader, Yacine; Moussaoui, Lotfi
    Introduction. This work presents a methodology for detecting inter-turn short circuit (ITSC) and broken rotor bars (BRB) fault in variable speed induction machine controlled by field oriented control. If any of these faults are not detected at an early stage, it may cause an unexpected shutdown of the industrial processes and significant financial losses. Purpose. For these reasons, it is important to develop a new diagnostic system to detect in a precautionary way the ITSC and BRB at various load condition. We propose the application of discrete wavelet transform to overcome the limitation of traditional technique for no-stationary signals. The novelty of the work consists in developing a diagnosis system that combines the advantages of both the discrete wavelet transform (DWT) and artificial neural network (ANN) to identify and diagnose defects, related to both ITSC and BRB faults. Methods. The suggested method involves analyzing the electromagnetic torque signal using DWT to calculate the stored energy at each level of decomposition. Then, this energy is applied to train neural network classifier. The accuracy of ANN based on DWT, was improved by testing different orthogonal wavelet functions on simulated signal. The selection process identified 5 pertinent wavelet energies, concluding that, Daubechies44 (db44) is the best suitable mother wavelet function for effectively detecting and classifying failures in machines. Results. We applied numerical simulations by MATLAB/Simulink software to demonstrate the validity of the suggested techniques in a closed loop induction motor drive. The obtained results prove that this method can identify and classify these types of faults under various loads of the machine.
  • Ескіз
    Документ
    Fault tolerant control of a permanent magnet synchronous machine using multiple constraints Takagi-Sugeno approach
    (Національний технічний університет "Харківський політехнічний інститут", 2022) Moussaoui, Lotfi; Aouaouda, Sabrina; Rouaibia, Reda
    Introduction. Fault diagnosis, and fault tolerant control issues are becoming very important to ensure a good supervision of systems and guarantee the safety of human operators and equipments even if system complexity increases. Problem. In fact, the presence of faults in actuators, sensors and processes can lead to system performance degradation, system breakdown, economic loss, and even disastrous situations. Furthermore, Actuator saturation or control input saturation is probably the most usual nonlinearity encountered in control engineering because of the physical impossibility of applying unlimited control signals and/or safety constraints. Purpose. This article is dedicated to the problem of fault tolerant control for constrained nonlinear systems described by a Takagi-Sugeno model. One of the interests of this type of models is the possibility of extend some tools and methods from linear system case to the nonlinear one. The novelty of the work consists in developing a fault tolerant control algorithm for a nonlinear Permanent Magnet Synchronous Machine model using an observer based state-feedback control technique in order to enhance fault and state estimation despite actuator saturation and system disturbances. Methods. Indeed a sensor fault detection observer based residual generator is synthesized with a guaranteed L₂ performance to attenuate the external disturbances effect from one side and to maximize the residual sensitivity to faults from the other side. Based on Lyapunov function, design conditions are formulated in terms of Linear Matrix Inequalities to ensure stability of the global system. Practical value. A detailed study concerning nonlinear permanent magnet synchronous machine model, which is consolidated by simulation results, is conducted to show the used algorithm’s effectiveness guarantying fault estimation and reconfiguration of the control law to maintain stable performance even in the presence of actuator faults, external perturbation and the phenomenon of actuator saturation.