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Fault detection and diagnosis methods have to deal with large variable data sets encountered in complex industrial systems. Solutions to this problem require multivariate statistics approaches often focused on the reduction of the space dimension. In this paper we propose a fault detection and estimation approach using Multivariate Kullback-Leibler Divergence (MKLD) to cope with the negative effects...
This paper addresses the problem of detecting voltage dips in Wind Turbine Generator connected to electrical grid. A procedure based on analysis of voltage indicators is proposed. It used the artificial neural network in order to extract the features (magnitudes and angle of each phase). The method is tested in simulation and the results approved its efficiency and rapidity. It could not only detect...
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