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In this paper we develop a fault detection, isolation and estimation method based on data-driven approach. Data-driven methods are effective for feature extraction and feature analysis using statistical techniques. In the proposal, the Principal Component Analysis (PCA) method is used to extract the features and to reduce the data dimension. Then, the Kullback-Leibler Divergence (KLD) is used to detect...
In this paper, we propose an overview of the Fault Detection and Diagnosis concept as the detection and characterisation of a hidden information as usually addressed in Data Hiding approaches. In fact, on one side Fault Detection and Diagnosis is generally studied as the detection and characterization of changes (abrupt or not) in a signal describing the behavior of a system. On the other side, data-hiding...
The aim of this paper is to present a fault detection and isolation procedure on a three phase inverter feeding an induction machine drive. The main goal of this classification is to help the supervising team for the monitoring and also for the maintenance. The monitoring increases the reliability of the drive and the accurate isolation reduces the time to repair and therefore reduces the maintenance...
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