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Thelaidjia T.,University of Guelma | Thelaidjia T.,Research Center in Industrial Technologies | Moussaoui A.,University of Guelma | Chenikher S.,University of Tebessa
Proceedings of 2015 7th International Conference on Modelling, Identification and Control, ICMIC 2015 | Year: 2015

This study concerns with fault diagnosis in rolling bearings using discrete wavelet transform (DWT), statistical parameters, independent component analysis (ICA) and support vector machine (SVM). The features for classification are extracted through using statistical parameters combined with energy obtained through the application of Db2-discrete wavelet transform at the fifth level of decomposition. After feature extraction, ICA is employed to select the relevant features. Finally an optimized SVM based on particle swarm optimization (PSO) is used for bearing fault decision. The obtained results proved the effectiveness of the proposed methodology for bearing faults diagnosis. © 2015 University of Al Qayrawan, Tunisia. Source

Nacereddine N.,Research Center in Industrial Technologies | Nacereddine N.,Dr. Yahia Fares University Center of Medea | Ziou D.,Universite de Sherbrooke
Advances in Intelligent Systems and Computing | Year: 2016

In this paper, a parametric histogram-based image segmentation method is used where the gray level histogram is considered as a finite mixture of asymmetric generalized Gaussian distribution (AGGD). The choice of AGGD is motivated by its flexibility to adapt the shape of the data including the asymmetry. Here, the method of moment estimation combined to the expectation–maximization algorithm (MME/EM) is originally used to estimate the mixture parameters. The proposed image segmentation approach is achieved in radiographic imaging where the image often presents an histogram with a complex shape. The experimental results provided in terms of histogram fitting error and region uniformity measure are comparable to those of the maximum likelihood method (MLE/EM) with the advantage that MME/EM method reveals to be more robust to the EM initialization than MLE/EM. © Springer International Publishing Switzerland 2016. Source

Thelaidjia T.,University of 08 Mai 1985 | Thelaidjia T.,Research Center in Industrial Technologies | Moussaoui A.,Laboratory of Electrical Engineering of Guelma | Chenikher S.,University of Tebessa
Engineering Solid Mechanics | Year: 2016

In this paper, a method for severity fault diagnosis of ball bearings is presented. The method is based on wavelet packet transform (WPT), statistical parameters, principal component analysis (PCA) and support vector machine (SVM). The key to bearing faults diagnosis is features extraction. Hence, the proposed technique consists of preprocessing the bearing fault vibration signal using statistical parameters and energy obtained through the application of Db8- WPT at the third level of decomposition. After feature extraction from vibration signal, PCA is employed for dimensionality reduction. Finally, particle swarm optimization with passive congregation-based support vector machine is used to classify seven kinds of bearing faults. The classification results indicate the effectiveness of the proposed method for severity faults diagnosis in ball bearings. © 2016 Growing Science Ltd. All rights reserved. Source

Ouadah M.,Polytechnic School of Algiers | Ouadah M.,Research Center in Industrial Technologies | Touhami O.,Polytechnic School of Algiers | Ibtiouen R.,Polytechnic School of Algiers
Progress In Electromagnetics Research M | Year: 2016

This paper diagnoses the effect of the AC current densities induced by the electromagnetic interferences between high voltage power line and buried power line on the cathodic protection performances of the X70 steel in the simulated soil. First, the induced voltage onto the pipeline was calculated for various power line configurations, separation distances between transmission line and pipeline and parallelism lengths. The induced AC current density was computed function to the induced voltage, soil resistivity, and holiday diameter. Then, the electrochemical characters of the X70 steel, at various AC current densities, are measured using the potentiodynamic method. The electrochemical parameters obtained by the electrochemical tests are used as boundary conditions in the cathodic protection simulation model. The results indicate that, under influence of AC current densities, the X70 steel is more susceptible to corrosion, and the cathodic protection is unable to maintain the protection potential. © 2016, Electromagnetics Academy. All rights reserved. Source

Merabti H.,Research Center in Industrial Technologies | Merabti H.,University of Mentouri Constantine | Belarbi K.,Polytechnic School of Algiers | Bouchemal B.,Research Center in Industrial Technologies
Journal of the Chinese Institute of Engineers, Transactions of the Chinese Institute of Engineers,Series A/Chung-kuo Kung Ch'eng Hsuch K'an | Year: 2015

The basic features of model-based predictive control (MBPC) make it an interesting candidate for the control of mobile robots. However, fast solution procedures remain a challenge for nonlinear MBPC problems such as the one arising in mobile robot control. Metaheuristics are general purpose heuristics which have been successful in solving difficult optimization problems in a reasonable computation time. In this work, we present a comparison between the uses of three different heuristics, namely particle swarm optimization (PSO), ant colony optimization, and gravitational search algorithm for the solution of the nonlinear MBPC for a mobile robot tracking trajectory with dynamic obstacle avoidance. The computation times obtained show that PSO is a feasible alternative for real-time applications. The MBPC based on the PSO is applied to controlling a LEGO mobile robot with encouraged results. © 2015 The Chinese Institute of Engineers Source

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