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RISS 인기검색어
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- 저자 : Ouassaid Mohammed (검색결과 5 건)
- 무료
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Nabil Ngote,Mohammed Ouassaid,Said Guedira,Mohamed Cherkaoui 대한전기학회 2015 Journal of Electrical Engineering & Technology Vol.10 No.6
Induction motors are widely used in industrial processes since they offer a very high degree of reliability. But like any other machine, they are vulnerable to faults, which if left unmonitored, might lead to an unexpected interruption at the industrial plant. Therefore, the condition monitoring of the induction motors have been a challenging topic for many electrical machine researchers. Indeed, the effectiveness of the fault diagnosis and prognosis techniques depends very much on the quality of the fault features selection. However, in induction-motor drives, rotor defects are the most complex in terms of detection since they interact with the supply frequency within a restricted band around this frequency, especially in the no-loaded case. To overcome this drawback, this paper deals with an efficient and new method to diagnose the induction-motor rotor fault based on the digital implementation of the monitoring algorithm based on the association of the Time Synchronous Averaging technique and Discrete Wavelet Transform. Experimental results are presented in order to show the effectiveness of the proposed method. The obtained results are largely satisfactory, indicating a promising industrial application of the combined “Time Synchronous Averaging – Discrete Wavelet Transform” approach.
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Ngote, Nabil,Ouassaid, Mohammed,Guedira, Said,Cherkaoui, Mohamed The Korean Institute of Electrical Engineers 2015 Journal of Electrical Engineering & Technology Vol.10 No.6
Induction motors are widely used in industrial processes since they offer a very high degree of reliability. But like any other machine, they are vulnerable to faults, which if left unmonitored, might lead to an unexpected interruption at the industrial plant. Therefore, the condition monitoring of the induction motors have been a challenging topic for many electrical machine researchers. Indeed, the effectiveness of the fault diagnosis and prognosis techniques depends very much on the quality of the fault features selection. However, in induction-motor drives, rotor defects are the most complex in terms of detection since they interact with the supply frequency within a restricted band around this frequency, especially in the no-loaded case. To overcome this drawback, this paper deals with an efficient and new method to diagnose the induction-motor rotor fault based on the digital implementation of the monitoring algorithm based on the association of the Time Synchronous Averaging technique and Discrete Wavelet Transform. Experimental results are presented in order to show the effectiveness of the proposed method. The obtained results are largely satisfactory, indicating a promising industrial application of the combined “Time Synchronous Averaging – Discrete Wavelet Transform” approach.
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Nabil Ngote,Said Guedira,Mohamed Cherkaoui,Mohammed Ouassaid 대한전기학회 2014 Journal of Electrical Engineering & Technology Vol.9 No.2
Induction motors are critical components in industrial processes since their failure usually lead to an unexpected interruption at the industrial plant. The studies of induction motor behavior during abnormal conditions and the possibility to diagnose different types of faults have been a challenging topic for many electrical machine researchers. In this regard, an efficient and new method to detect the induction motor-fault may be the application of the Time Synchronous Averaging (TSA) to the stator current Park’s Vector. The aim of this paper is to present a methodology by which defects in a three-phase wound rotor induction motor can be diagnosed. By exploiting the cyclostationarity characteristics of electrical signals, the TSA method is applied to the stator current Park’s Vector, allowing the monitoring of the induction motor operation. Simulation and experimental results are presented in order to show the effectiveness of the proposed method. The obtained results are largely satisfactory, indicating a promising industrial application of the hybrid Park’s Vector-TSA approach.
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Game Theory Approach for Energy Consumption Scheduling of a Community of Smart Grids
Naji El Idrissi Rajaa,Ouassaid Mohammed,Maaroufi Mohamed 대한전기학회 2023 Journal of Electrical Engineering & Technology Vol.18 No.4
This study analyzes the potential of an independent method of dynamic pricing schemes to reduce the peak demand in the neighborhood area. For this, this work develops a collective energy consumption scheduling (CECS) algorithm in the residential sector based on a combination of energy consumption plans under a bi-level game theory method. The local level is responsible of gathering internal users’ data and reducing the energy consumption in each residential building. The central level is the external demand management system that is focused on modeling a coalition between the local load management modules, as well as giving the redistributed demand profile to increase the global profit through a peak load minimization, financial gain and peak-to-average-ratio reduction. Four controllable appliances are included in load shifting and time activation cycling: clothes dryer units, heating, ventilation and air conditioning systems, electric water heater, and electric vehicle. The principle of the proposed CECS method relies on the flexibility of the user requirement that presents one of the contributions of this study. It proposes a novel framework for determining optimal non-static load management strategies, in which consumers can change their daily power demand patterns depending on their routines, preferences and requirements. Numerical results show that time-varying schemes encourage customers to condense their electricity consumption within low-price periods. However, by incorporating the proposed approach of coordinated scheduling algorithm significant profits in the whole and single level are demonstrated. Simulations infer that given the same load profiles, the proposed framework outperforms the non-coordinated strategy leading to important rates in total peak load minimization, total saving in electricity bills and reduction of peak-to-average-ratio.
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Ngote, Nabil,Guedira, Said,Cherkaoui, Mohamed,Ouassaid, Mohammed The Korean Institute of Electrical Engineers 2014 Journal of Electrical Engineering & Technology Vol.9 No.2
Induction motors are critical components in industrial processes since their failure usually lead to an unexpected interruption at the industrial plant. The studies of induction motor behavior during abnormal conditions and the possibility to diagnose different types of faults have been a challenging topic for many electrical machine researchers. In this regard, an efficient and new method to detect the induction motor-fault may be the application of the Time Synchronous Averaging (TSA) to the stator current Park's Vector. The aim of this paper is to present a methodology by which defects in a three-phase wound rotor induction motor can be diagnosed. By exploiting the cyclostationarity characteristics of electrical signals, the TSA method is applied to the stator current Park's Vector, allowing the monitoring of the induction motor operation. Simulation and experimental results are presented in order to show the effectiveness of the proposed method. The obtained results are largely satisfactory, indicating a promising industrial application of the hybrid Park's Vector-TSA approach.
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