Research Center in Industrial Technologies

Algiers, Algeria

Research Center in Industrial Technologies

Algiers, Algeria
Time filter
Source Type

Kouadri-Henni A.,CNRS Civil and Mechanical Engineering Laboratory | Barrallier L.,Arts et Metiers ParisTech | Badji R.,Research Center in Industrial Technologies
MATEC Web of Conferences | Year: 2016

The objective of this study was to evaluate the residual stresses of FSW welding magnesium alloys (AZ31). The results show that the FSW processes lead to the formation of several distinct zones with differing mechanical properties. The residual stresses evolution have been explained by the heterogeneous modifications of the microstructure particularly a marked decrease in the grain size, a high modification of the crystallographic texture and the different anisotropic properties resulting from plasticity induced by the FSW process. © The Authors, published by EDP Sciences, 2016.

Hichem M.,Research Center in Industrial Technologies | Tahar B.,Annaba University
International Journal of Modelling, Identification and Control | Year: 2017

According to its high robustness, the use of doubly-fed induction generators in the wind energy conversion takes an important place in the world of production of electrical energy. This type of conversion became very attractive because of its manufacturing environments, low cost and operation with an easily available power supply. The increase interest in wind energy conversion has been accompanied by efforts to improve reliability, effective condition monitoring and better efficiency. In this work, a new technique is proposed for monitoring and detection of inter-turn short-circuit ITSC and open phase circuits in the stator or rotor windings of wind turbines based on doubly-fed induction generator The principle of the suggested technique is based on the acquisition of the stator and the rotor currents of a doubly-fed induction generator with the aim to calculate the values of root mean square amplitude, in addition to the knowledge expressed in rules and membership function. This technique is verified using simulations performed via the model of doubly-fed induction generators built in MATLAB ® Simulink. Copyright © 2017 Inderscience Enterprises Ltd.

Boutiche Y.,Research Center in Industrial Technologies | Boutiche Y.,Blida University | Abdesselam A.,Sultan Qaboos University
IET Image Processing | Year: 2017

Active contours are usually based on the optimisation of energy functionals that are built to attract the curve towards the objects' boundaries. This study describes a hybrid region-based active contours technique that uses global means to define the global fitting energy and local means and variances to define the local fitting energy. The optimisation of the functional is performed by applying a sweeping-principle algorithm, which avoids solving any partial differential equation and removes the need for any stability conditions. Furthermore, sweeping-principle algorithm is not based on the computation of derivatives, which allows using a binary level set function during the minimisation process instead of the signed distance function, consequently this removes the need for the distance regularisation term, avoiding its subtle side effects and speeding up the optimisation process. Successful and accurate segmentation results are obtained on synthetic and real images with a significant gain in the CPU execution time when compared with the minimisation via the commonly used gradient descent method. © The Institution of Engineering and Technology.

Bouzida A.,University of Boumerdès | Abdelli R.,Beiaia University | Ouadah M.,Research Center in Industrial Technologies
Proceedings of 2016 8th International Conference on Modelling, Identification and Control, ICMIC 2016 | Year: 2016

Several techniques for estimating power losses in insulated-gate bipolar transistors (IGBTs), diodes and MOSFETs are known. Most of the approaches in the literature deal with PWM switching technique. In this paper presents a feasible loss model to estimate IGBT losses in a switching operation. The loss model is coupled to RC (Foster) Network using the Thermal Impedance. This paper investigates the power losses in IGBT's and associated Diodes as a function of the circuit and the temperature variation during operation. A full presentation of the electro-thermal model has been developed and simulated. © 2016 University of MEDEA, Algeria.

Tala-Ighil N.,Research Center in Industrial Technologies | Fillon M.,University of Poitiers
IOP Conference Series: Materials Science and Engineering | Year: 2017

This study investigates the evolution of the main bearing performance of partially and fully textured hydrodynamic journal bearing. The viscosity effect is also analysed by the mean of numerical simulations for two types of oil: the oil 1 (ISO VG 32, 31.3 cSt at 40 °C) has a lower viscosity than oil 2 (ISO VG 100, 93 cSt at 40 °C). Reynolds equation is solved by finite difference and Gauss-Seidel methods with over-relaxation for various operating conditions. It is shown that, under hydrodynamic lubrication regime, the improvement of the most important characteristics (the friction coefficient and minimum film thickness) of a textured journal bearing depend strongly on the lubricant viscosity and the journal rotational speed. The fully textured journal bearing is highly favorable at very low speeds while the partially textured journal bearing is more suitable for slightly higher speeds. The gain in bearing performance due to the texturing of the bushing disappears at a critical speed of the journal and then, for higher rotational speeds, the presence of textures becomes detrimental. © Published under licence by IOP Publishing Ltd.

Attoui I.,Research Center in Industrial Technologies | Fergani N.,Research Center in Industrial Technologies | Boutasseta N.,Research Center in Industrial Technologies | Oudjani B.,Research Center in Industrial Technologies | Deliou A.,Research Center in Industrial Technologies
Journal of Sound and Vibration | Year: 2017

In order to fault diagnosis of ball bearing that is one of the most critical components of rotating machinery, this paper presents a time–frequency procedure incorporating a new feature extraction step that combines the classical wavelet packet decomposition energy distribution technique and a new feature extraction technique based on the selection of the most impulsive frequency bands. In the proposed procedure, firstly, as a pre-processing step, the most impulsive frequency bands are selected at different bearing conditions using a combination between Fast-Fourier-Transform FFT and Short-Frequency Energy SFE algorithms. Secondly, once the most impulsive frequency bands are selected, the measured machinery vibration signals are decomposed into different frequency sub-bands by using discrete Wavelet Packet Decomposition WPD technique to maximize the detection of their frequency contents and subsequently the most useful sub-bands are represented in the time-frequency domain by using Short Time Fourier transform STFT algorithm for knowing exactly what the frequency components presented in those frequency sub-bands are. Once the proposed feature vector is obtained, three feature dimensionality reduction techniques are employed using Linear Discriminant Analysis LDA, a feedback wrapper method and Locality Sensitive Discriminant Analysis LSDA. Lastly, the Adaptive Neuro-Fuzzy Inference System ANFIS algorithm is used for instantaneous identification and classification of bearing faults. In order to evaluate the performances of the proposed method, different testing data set to the trained ANFIS model by using different conditions of healthy and faulty bearings under various load levels, fault severities and rotating speed. The conclusion resulting from this paper is highlighted by experimental results which prove that the proposed method can serve as an intelligent bearing fault diagnosis system. © 2017 Elsevier Ltd

Bendjama H.,Research Center in Industrial Technologies | Mahdi D.,University Of Msila
Journal of Failure Analysis and Prevention | Year: 2016

Non-destructive testing (NDT) is a highly valuable technique in evaluation and evolution of materials and products. X-ray imaging is an important NDT technique that is used widely in the metal industry in order to control the quality of materials. Sometimes it may be difficult to get a measurement. The simulation of X-ray imaging is often performed using computer codes. This paper presents a new simulation method for materials diagnosis. The simulation is based primarily on the X-ray attenuation law and it is performed using a combination between Monte Carlo method and multi-layer perceptron neural network. The main goal of the proposed method is to obtain more detailed information about the state of the materials. © 2016 ASM International

Nacereddine N.,Research Center in Industrial Technologies | Nacereddine N.,Dr. Yahia Fares University Center of Médéa | Ziou D.,Université 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.

Merabet H.,Research Center in Industrial Technologies | Bahi T.,Annaba University
EEA - Electrotehnica, Electronica, Automatica | Year: 2016

Doubly-fed induction generators are being used extensively in wind energy conversion systems. Efforts are being made to effectively adopt existing condition monitoring and fault diagnostic techniques for these systems. We consider in this paper to take account of the specificities and characteristics of the doubly-fed induction generator, for develop an analytical model that describes as precisely as possible the machine performance in healthy and machine with different eccentricity faults types. In this paper, we propose a method for the eccentricity diagnosis fault based on the stator current analysis during the start-up using this wavelet method enables faults eccentricity detection and isolation of this fault in rotor by analysing the frequency spectrum. This study showed that the application of this technique offered reliable and acceptable results for diagnosis detection and faults. © 2016, ICPE Electra Publishing House. All rights reserved.

Boutiche Y.,Research Center in Industrial Technologies
Proceedings of 2016 SAI Computing Conference, SAI 2016 | Year: 2016

A major problem with image segmentation is the building of model that is able to deal with all kind of image. This is due to the diversity of the image sources. However, the aim is to widen, as much as possible, the capability of the model to segment several image modalities. Hybridization between some models seems a good alternative to achieve that. In this paper, functional that incorporate several kinds of image information is used: edge detector function, local means and variances, and global means. Such choice allows getting successful segmentation results as it will be shown in the experimental section. © 2016 IEEE.

Loading Research Center in Industrial Technologies collaborators
Loading Research Center in Industrial Technologies collaborators