New fusion and selection approaches for estimating the remaining useful life using Gaussian process regression and induced ordered weighted averaging operators

In this paper, we propose new fusion and selection approaches to accurately predict the remaining useful life. The fusion scheme is built upon the combination of outcomes delivered by an ensemble of Gaussian process regression models. Each regressor is characterized by its own covariance function and initial hyperparameters. In this context, we adopt the induced ordered weighted averaging as a fusion tool to achieve such combination. Two additional fusion techniques based on the simple averaging and the ordered weighted averaging operators besides a selection approach are implemented. The differences between adjacent elements of the raw data are used for training instead of the original values. Experimental results conducted on lithium-ion battery data report a significant improvement in the obtained results. This work may provide some insights regarding the development of efficient intelligent fusion alternatives for further prognostic advances.     

Structural,Electrical and Optical Properties of PVC/ZnTe Nanocomposite Thin Films

Journal of Inorganic and Organometallic Polymers and Materials - ZnTe nanoparticles (NPs) were synthesized using hydrothermal method and then were dispersed in poly(vinyl-chloride) (PVC) to prepare...     

Real time simulation of nonlinear generalized predictive control for wind energy conversion system with nonlinear observer

In order to make a wind power generation truly cost-effective and reliable, an advanced control techniques must be used. In this paper, we develop a new control strategy, using nonlinear generalized predictive control (NGPC) approach, for DFIG-based wind turbine. The proposed control law is based on two points: NGPC-based torque-current control loop generating the rotor reference voltage and NGPC-based speed control loop that provides the torque reference. In order to enhance the robustness of the controller, a disturbance observer is designed to estimate the aerodynamic torque which is considered as an unknown perturbation. Finally, a real-time simulation is carried out to illustrate the performance of the proposed controller.     

Numerical multi-scale modeling for textile woven fabric against ballistic impact

In this study, a FEM analysis has been carried out to find out pertinent multi-scale model for an investigation of a ballistic impact on 2D KM2® plain-woven fabrics. Multi-scale models are a combination between macroscopic and mesoscopic models. This study aims at testing a multi-scale model in order to minimize the computing time. Three configurations were analyzed by varying the ratio of macroscopic and mesoscopic areas: 75.3–24.7%, 65.5–34.5%, 56.3–43.7% with two impact velocities 60 m/s and 245 m/s. In these multi-scale models, the continuity in macroscopic–mesoscopic interfaces is ensured by checking the evolution of global displacements of the fabric during impact. The effect of the macroscopic area of multi-scale models on the ballistic performance of the fabric is also investigated. The optimal multi-scale model was validated by comparison with results obtained from a mesoscopic model in terms of the evolutions of the projectile velocity, energy forms, the overall behavior of the fabric during impact and the force applied on the projectile. The failure criterion Forming Limited Diagram (FLD) is suggested for bundle failure. The observed damage mechanisms of the fabric during penetration time of the projectile are discussed and compared among numerical models.     

Structure,tribotechnical, and thermophysical characteristics of the fluoroplastic carbonnanotubes material

In this work, we studied a nanocomposite material made from fluoroplastic which contains 20 wt.% multi-walled nanotubes. In order to complete the present work, we have used different thermodynamic and mechanical techniques. The introduction of nanotubes in the F4 polymer matrix has completely changed the tribological and thermodynamic properties of the studied nanocomposite material. The compression strength becomes 20% higher than that of the F4 polymer matrix. Meanwhile the wear resistance achieves an order of magnitude 100 times greaterthan that of F4. Moreover, a friction coefficient is about 25% to 30% lower than that of a similar material and especially that of F4 material. Differential scanning calorimetric study showed that the glassy phase transition appears at about 330°C, which confirms that the degradation of the studied nanocomposite occurs at relatively higher temperature. This result confirms the one concerning the change in tribological properties. Dilatometric study revealed that the thermal expansion coefficient has been increased. The observed relative elongation measurement change depends on the direction along which the measurement has been done and confirms, in turn, the anisotropic character of the studied material. These results suggest that the metallic materials could be replaced by nanocomposite compounds which present good physical properties.     

Silicon nanowire arrays-induced graphene oxide reduction under UV irradiation

This paper reports on efficient UV irradiation-induced reduction of exfoliated graphene oxide. Direct illumination of an aqueous solution of graphene oxide at λ = 312 nm for 6 h resulted in the formation of graphene nanosheets dispersible in water. X-Ray photoelectron spectroscopy (XPS), UV-vis spectroscopy, atomic force microscopy (AFM) and electrochemical measurements (cyclic voltammetry and electrochemical impedance spectroscopy) suggest a restoration of the sp(2) carbon network. The results were compared with graphene nanosheets prepared by photochemical irradiation of a GO aqueous solution in the presence of hydrogenated silicon nanowire (SiNW) arrays or silicon nanowire arrays decorated with silver (SiNW/Ag NPs) or copper nanoparticles (SiNW/Cu NPs). Graphene nanosheets obtained by illumination of the GO aqueous solution at 312 nm for 6 h in the presence of SiNW/Cu NPs exhibited superior electrochemical charge transfer characteristics. This is mainly due to the higher amount of sp(2)-hybridized carbon in these graphene sheets found by XPS analysis. The high level of extended conjugated carbon network was also evident by the water insoluble nature of the resulting graphene nanosheets, which precipitated upon photochemical reduction.     

ANFIS-based approach to studying subthreshold behavior including the traps effect for nanoscale thin-film DG MOSFETs

A fuzzy framework based on an adaptive network fuzzy inference system(ANFIS) is proposed to evaluate the relative degradation of the basic subthreshold parameters due to hot-carrier effects for nanoscale thin-film double-gate(DG) MOSFETs.The effect of the channel length and thickness on the resulting degradation is addressed, and 2-D numerical simulations are used for the elaboration of the training database.Several membership function shapes are developed,and the best one in terms of accuracy is selected.The predicted results agree well with the 2-D numerical simulations and can be efficiently used to investigate the impact of the interface fixed charges and quantum confinement on nanoscale DG MOSFET subthreshold behavior.Therefore,the proposed ANFIS-based approach offers a simple and accurate technique to study nanoscale devices,including the hot-carrier and quantum effects.     

Structural feature-based evaluation method of binarization techniques for word retrieval in the degraded Arabic document images

One of the most important and necessary steps in the process of document analysis and recognition is the binarization, which allows extracting the foreground from the background. Several binarization techniques have been proposed in the literature, but none of them was reliable for all image types. This makes the selection of one method to apply in a given application very difficult. Thus, performance evaluation of binarization algorithms becomes therefore vital. In this paper, we are interested in the evaluation of binarization techniques for the purpose of retrieving words from the images of degraded Arabic documents. A new evaluation methodology is proposed. The proposed evaluation methodology is based on the comparison of the visual features extracted from the binarized document images with ground truth features instead of comparing images between themselves. The most appropriate thresholding method for each image is the one for which the visual features of the identified words in the image are “closer” to the features of the reference words. The proposed technique was used here to assess the performances of eleven algorithms based on different approaches on a collection of real and synthetic images.