Ghaleb Hoblos

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— This paper proposes a general method for dealing with state estimation under nonlinear state soft inequality constraints. This method is based on the projection approach, and then has the advantage to be compatible with any kind of state estimator. In order to be taken into account, the nonlinear constraints are linearized about the constrained state(More)
This paper aims at proposing an algorithm that improves fault detection, through on-line monitoring, in industrial systems. This is accomplished by analyzing and detecting frequency changes in signal generated by these systems. Early fault detection, which reduces the possibility of catastrophic damage, is possible, by detecting the changes of(More)
This paper deals with the state estimation of a strongly nonlinear system. In a noisy state space representation setting, Central Difference Kalman Filter, Ensemble Kalman Filter and Particle Filter are tested on a second order system. The choice of estimators parameters is then discussed, and their behaviour in relation to noise is studied, in order to(More)
Feature selection is an essential step for data classification used in fault detection and diagnosis processes. In this work, a new approach is proposed, which combines a feature selection algorithm and a neural network tool for leak detection and characterization tasks in diesel engine air paths. The Chi square classifier is used as the feature selection(More)