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In this paper we focus our attention on the tracking of faulty lines emerging in the stator current in an induction motor. The defect retained is the appearance of a problem of outer race fault in ball bearings. To do that, a particle swarm optimization algorithm is used in order to track these faulty lines. Consequently, we would be able to inform the operator on the presence or not of a defect thanks...
Electric drives condition monitoring is essential to optimize maintenance operations and to increase reliability levels. This paper presents a diagnosis method for electrical faults detection. Firstly some signatures representing induction motor thermal heating are developed. Indeed a motor provides normal losses (mechanical, electrical, magnetic, etc.) as well as additional losses due to some faults...
This paper shows a new signature for detection of rotor bar faults in induction motors trough external magnetic field analysis. The proposed method is based on the variations of the axial flux density in the presence of rotor faults, particularly regarding the low frequency part of the frequency spectrum. The analysis of the external magnetic field variation in low frequency is realized through a...
This paper is a continuation of a previous work regarding the induction motors diagnosis problem. An on-line fault detection strategy has been proposed using a graphical signature generation tool. In this work, the graphical tool is used for an off-line diagnosis including isolation and estimation. The underlying diagnosis problem corresponds to variations affecting three of system's parameters, namely,...
The authors propose a new diagnosis method for on-line broken bars detection by parameters estimation. For predictive detection, Kalman filtering algorithm has been adapted to take into account the on-line parameters deviations in faulty case. Within the framework of the diagnosis of the rotor defects, it is difficult to conduct experimental tests to validate the on-line identification of such default...
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