Fault identification in distribution lines using intelligent systems and statistical methods

The main objective involved with this paper consists of presenting the results obtained from the application of artificial neural networks and statistical tools in the automatic identification and classification process of faults in electric power distribution systems. The developed techniques to treat the proposed problem have used, in an integrated way, several approaches that can contribute to the successful detection process of faults, aiming that it is carried out in a reliable and safe way. The compilations of the results obtained from practical experiments accomplished in a pilot distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder. © 2006 IEEE.

Intelligent alarm processing

This paper presents the analysis that have been carried out in the alarm system of the DCRanger EMS. The intention of this study is to present the problem of alarm processing in electric energy control centers, its various aspects and operational difficulties due to operator needs. Some tests are produced in order to identify the desirable features an alarm system should possess in order to be of effective help in the operative duty. © 2006 IEEE.

Towards intelligent manufacturing

This article describes the application of an Artificial Intelligence Planner in a robotized assembly cell that can be integrated to a Flexible Manufacturing System. The objective is to allow different products to be automatically assembled in a single production line with no pre-established assembly plans. The planner function is to generate action plans to the robot, in real time, from two input information: the initial state (disposition of parts of the product in line) and the final state (configuration of the assembled product). Copyright © 2007 IFAC.

Infrared face recogniton by optimum-path forest

This paper presents a novel, fast and accurate appearance-based method for infrared face recognition. By introducing the Optimum-Path Forest classifier, our objective is to get good recognition rates and effectively reduce the computational effort. The feature extraction procedure is carried out by PCA, and the results are compared to two other well known supervised learning classifiers; Artificial Neural Networks and Support Vector Machines. The achieved performance asserts the promise of the proposed framework. ©2009 IEEE.

QCD phenomenology with infrared finite SDE solutions

Recent progress in the solution of Schwinger-Dyson equations (SDE), as well as lattice simulation of pure glue QCD, indicate that the gluon propagator and coupling constant are infrared (IR) finite. We discuss how this non-perturbative information can be introduced into the QCD perturbative expansion in a consistent scheme, showing some examples of tree level hadronic reactions that successfully fit the experimental data with the gluon propagator and coupling constant depending on a dynamically generated gluon mass. This infrared mass scale acts as a natural cutoff and eliminates some of the ad hoc parameters usually found in perturbative QCD calculations. The application of these IR finite Green's functions in the case of higher order terms of the perturbative expansion is commented. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike Licence.

An intelligent system to detect drilling problems through drilled cuttings return analysis

Cuttings return analysis is an important tool to detect and prevent problems during the petroleum well drilling process. Several measurements and tools have been developed for drilling problems detection, including mud logging, PWD and downhole torque information. Cuttings flow meters were developed in the past to provide information regarding cuttings return at the shale shakers. Their use, however, significantly impact the operation including rig space issues, interferences in geological analysis besides, additional personel required. This article proposes a non intrusive system to analyze the cuttings concentration at the shale shakers, which can indicate problems during drilling process, such as landslide, the collapse of the well borehole walls. Cuttings images are acquired by a high definition camera installed above the shakers and sent to a computer coupled with a data analysis system which aims the quantification and closure of a cuttings material balance in the well surface system domain. No additional people at the rigsite are required to operate the system. Modern Artificial intelligence techniques are used for pattern recognition and data analysis. Techniques include the Optimum-Path Forest (OPF), Artificial Neural Network using Multilayer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC). Field test results conducted on offshore floating vessels are presented. Results show the robustness of the proposed system, which can be also integrated with other data to improve the efficiency of drilling problems detection. Copyright 2010, IADC/SPE Drilling Conference and Exhibition.

Experimental observation of infrared spectral enlargement in As 2S3 suspended core microstructured fiber

The development of chalcogenide glasses fibers for application in the infrared wavelength region between 1 and 10 μm is a big opportunity. More particularly, the possibility to generate efficient non linear effects above 2 μm is a real challenge. We present in this work the elaboration and optical characterizations of suspended core microstructured optical fibers elaborated from the As2S3 chalcogenide glass. As an alternative to the stack and draw process a mechanical machining has been used to the elaboration of the preforms. The drawing of these preforms into fibers allows reaching a suspended core geometry, in which a 2.5 μm diameter core is linked to the fiber clad region by three supporting struts. The zero dispersion wavelength is thus shifted towards 2 μm. At 1.55 μm our fibers exhibit a dispersion around -250 ps/nm/km. Their background level of losses is below 0,5 dB/m. By pumping them at 1.55 μm with a ps source, we observe self phase modulation as well as Raman generation. Finally a strong spectral enlargement is obtained with an average output power of - 5 dbm. © 2010 SPIE.

Infrared thermography applied to the evaluation of metabolic heat loss of chicks fed with different energy densities

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A multi-agent architecture for intelligent data analysis

The present study introduces a multi-agent architecture designed for doing automation process of data integration and intelligent data analysis. Different from other approaches the multi-agent architecture was designed using a multi-agent based methodology. Tropos, an agent based methodology was used for design. Based on the proposed architecture, we describe a Web based application where the agents are responsible to analyse petroleum well drilling data to identify possible abnormalities occurrence. The intelligent data analysis methods used was the Neural Network.

HW/SW for an intelligent transducer network based on IEEE 1451 standard

This work describes a hardware/software co-design system development, named IEEE 1451 platform, to be used in process automation. This platform intends to make easier the implementation of IEEE standards 1451.0, 1451.1, 1451.2 and 1451.5. The hardware was built using NIOS II processor resources on Alteras Cyclone II FPGA. The software was done using Java technology and C/C++ for the processors programming. This HW/SW system implements the IEEE 1451 based on a control module and supervisory software for industrial automation. © 2011 Elsevier B.V.

Structural refinement, growth mechanism, infrared/Raman spectroscopies and photoluminescence properties of PbMoO4 crystals

Lead molybdate (PbMoO4) crystals were synthesized by the co-precipitation method at room temperature and then processed in a conventional hydrothermal (CH) system at low temperature (70 °C for different times). These crystals were structurally characterized by X-ray diffraction (XRD), Rietveld refinement, micro-Raman (MR) and Fourier transformed infrared (FT-IR) spectroscopies. Field emission scanning electron microscopy images were employed to observe the shape and monitor the crystal growth process. The optical properties were investigated by ultraviolet-visible (UV-Vis) absorption and photoluminescence (PL) measurements. XRD patterns and MR spectra indicate that these crystals have a scheelite-type tetragonal structure. Rietveld refinement data possibilities the evaluation of distortions in the tetrahedral [MoO 4] clusters. MR and FT-IR spectra exhibited a high mode ν1(Ag) ascribed to symmetric stretching vibrations as well as a large absorption band with two modes ν3(Eu and Au) related to anti-symmetric stretching vibrations in [MoO 4] clusters. Growth mechanisms were proposed to explain the stages involved for the formation of octahedron-like PbMoO4 crystals. UV-Vis absorption spectra indicate a reduction in optical band gap with an increase in the CH processing time. PL properties of PbMoO4 crystals have been elucidated using a model based on distortions of tetrahedral [MoO4] clusters due to medium-range intrinsic defects and intermediary energy levels (deep and shallow holes) within the band gap. © 2012 Elsevier Ltd. All rights reserved.

Upconversion luminescence in Er3+ doped Ga10Ge 25S65 glass and glass-ceramic excited in the near-infrared

The infrared-to-visible frequency upconversion was investigated in Er 3+-doped Ga10Ge25S65 glass and in the transparent glass-ceramic obtained by heat-treatment of the glass above its glass-transition temperature. Continuous-wave and pulsed lasers operating at 980 nm and 1480 nm were used as excitation sources. The green (2H 11/2 → 4I15/2; 4S3/2 → 4I15/2) and red (4F9/2 → 4I15/2) photoluminescence (PL) signals due to the Er3+ ions were characterized. The PL decay times were influenced by energy transfer among Er3+ ions, by cross-relaxation processes and by energy transfer from the Er3+ ions to the host material. The PL from the Er3+ ions hosted in the crystalline phase was distinguished only when the glass-ceramic was excited by the 1480 nm pulsed laser. The excitation pathways responsible for the green and red PL bands are discussed to explain the differences between the spectra observed under continuous-wave and pulsed excitation. © 2013 American Institute of Physics.

Infrared to visible up-conversion emission in Er3+/Yb 3+ codoped fluoro-phosphate glass-ceramics

Erbium Er3+ and ytterbium Yb3+ codoped fluoro-phosphate glasses belonging to the system NaPO3-YF 3-BaF2-CaF2 have been prepared by the classical melt-quenching technique. Glasses containing up to 10 wt% of erbium and ytterbium fluorides have been obtained and characterized using differential scanning calorimetry (DSC) and UV-visible and near-infrared spectroscopy. Transparent and homogeneous glass-ceramics have been then reproducibly synthetized by appropriate heat treatment above glass transition temperature of a selected parent glass. Structural investigations of the crystallization performed through X-ray diffractometry (XRD) and scanning electron microscopy (SEM) have evidenced the formation of fluorite-type cubic crystals based during the devitrification process. Finally, infrared to visible up-conversion emission upon excitation at 975 nm has been studied on the Er3+ and Yb 3+ codoped glass-ceramics as a function of thermal treatment time. A large enhancement of intensity of the up-conversion emissions-about 150 times- has been observed in the glass-ceramics if compared to the parent glass one, suggesting an incorporation of the rare-earth ions (REI) into the crystalline phase. © 2012 The American Ceramic Society.

Development and validation of an environmentally friendly attenuated total reflectance in the mid-infrared region method for the determination of ethanol content in used engine lubrication oil

Lubricating oils are crucial in the operation of automotive engines because they both reduce friction between moving parts and protect against corrosion. However, the performance of lubricant oil may be affected by contaminants, such as gasoline, diesel, ethanol, water and ethylene glycol. Although there are many standard methods and studies related to the quantification of contaminants in lubricant oil, such as gasoline and diesel oil, to the best of our knowledge, no methods have been reported for the quantification of ethanol in used Otto cycle engine lubrication oils. Therefore, this work aimed at the development and validation of a routine method based on partial least-squares multivariate analysis combined with attenuated total reflectance in the mid-infrared region to quantify ethanol content in used lubrication oil. The method was validated based on its figures of merit (using the net analyte signal) as follows: limit of detection (0.049%), limit of quantification (0.16%), accuracy (root mean square error of prediction=0.089% w/w), repeatability (0.05% w/w), fit (R 2 =0.9997), mean selectivity (0.047), sensitivity (0.011), inverse analytical sensitivity (0.016% w/w-1) and signal-to-noise ratio (max: 812.4 and min: 200.9). The results show that the proposed method can be routinely implemented for the quality control of lubricant oils. © 2013 Elsevier B.V. All rights reserved.