M. Drif

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Feature Selection is an important task which can affect the performance of pattern classification and recognition. In this paper, we present a feature selection algorithm based on genetic algorithm optimization. The algorithm adopts classifier performance and the number of the selected features as heuristic information, and selects the optimal feature(More)
This paper firstly presents a modelling and simulation study concerning the occurrence of airgap eccentricity in three-phase induction motors. For that purpose, the winding function approach is considered. Then, the instantaneous non-active power signature analysis is used as a new tool for the detection of mixed airgap eccentricity condition in operating(More)
In the last years, face verification has gained a great interest in the pattern recognition community and in many application fields. It is among the most attractive research areas because face images can be captured in a non-intrusive way. Many algorithms have been developed in this area, among them the Principal Component Analysis (PCA) is a typical face(More)
In this paper a new fault detection technique based on the instantaneous power factor signature analysis is proposed for the diagnosis of rotor cage faults in three-phase induction motors. A mathematical model based on the Winding Function Approach was used for the simulation of this type of fault and experimental tests were carried out on an induction(More)
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