Metodologia de localização de defeitos em redes subterrâneas integrando PSCAD/EMTDC e sistemas inteligentes

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A New Approach for Real Time Fault Diagnosis in Induction Motors Based on Vibration Measurement

Condition monitoring is used to increase machinery availability and machinery performance, reducing consequential damage, increasing machine life, reducing spare parts inventories, and reducing breakdown maintenance. An efficient real time vibration measurement and analysis instruments is capable of providing warning and predicting faults at early stages. In this paper, a new methodology for the implementation of vibration measurement and analysis instruments in real time based on circuit architecture mapped from a MATLAB/Simulink model is presented. In this study, signal processing applications such as FIR filters and fast Fourier transform are treated as systems, which are implemented in hardware using a system generator toolbox, which translates a Simulink model in a hardware description language - HDL for FPGA implementations.

Robust fault diagnosis in power distribution systems based on fuzzy ARTMAP neural network-aided evidence theory

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

Improved Fault Location on Distribution Feeders Based on Matching During-Fault Voltage Sags

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Automation in fault detection using neural network and model updating

In this article, an implementation of structural health monitoring process automation based on vibration measurements is proposed. The work presents an alternative approach which intent is to exploit the capability of model updating techniques associated to neural networks to be used in a process of automation of fault detection. The updating procedure supplies a reliable model which permits to simulate any damage condition in order to establish direct correlation between faults and deviation in the response of the model. The ability of the neural networks to recognize, at known signature, changes in the actual data of a model in real time are explored to investigate changes of the actual operation conditions of the system. The learning of the network is performed using a compressed spectrum signal created for each specific type of fault. Different fault conditions for a frame structure are evaluated using simulated data as well as measured experimental data.

An approach based on neural networks for identification of fault sections in radial distribution systems

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 radial distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder.

Signal classification of submerged aquatic vegetation based on the hemispherical-conical reflectance factor spectrum shape in the yellow and red regions

The water column overlying the submerged aquatic vegetation (SAV) canopy presents difficulties when using remote sensing images for mapping such vegetation. Inherent and apparent water optical properties and its optically active components, which are commonly present in natural waters, in addition to the water column height over the canopy, and plant characteristics are some of the factors that affect the signal from SAV mainly due to its strong energy absorption in the near-infrared. By considering these interferences, a hypothesis was developed that the vegetation signal is better conserved and less absorbed by the water column in certain intervals of the visible region of the spectrum; as a consequence, it is possible to distinguish the SAV signal. To distinguish the signal from SAV, two types of classification approaches were selected. Both of these methods consider the hemispherical-conical reflectance factor (HCRF) spectrum shape, although one type was supervised and the other one was not. The first method adopts cluster analysis and uses the parameters of the band (absorption, asymmetry, height and width) obtained by continuum removal as the input of the classification. The spectral angle mapper (SAM) was adopted as the supervised classification approach. Both approaches tested different wavelength intervals in the visible and near-infrared spectra. It was demonstrated that the 585 to 685-nm interval, corresponding to the green, yellow and red wavelength bands, offered the best results in both classification approaches. However, SAM classification showed better results relative to cluster analysis and correctly separated all spectral curves with or without SAV. Based on this research, it can be concluded that it is possible to discriminate areas with and without SAV using remote sensing. © 2013 by the authors; licensee MDPI, Basel, Switzerland.

Anderson localization and momentum-space entanglement

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

Testicular arteries systematization based on different levels of scrotal configuration in caprines

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Study of the interaction between cardiolipin bilayers and methylene blue in polymer-based Layer-by-Layer and Langmuir films applied as membrane mimetic systems

An increase of the reports involving mimetic systems has been observed. Briefly, these systems use biological phospholipids to exploit specific interactions between membrane-models and drugs. Here, the Layer-by-Layer (LbL) and Langmuir techniques were used to investigate the interaction between cardiolipin (CLP-negative phospholipid) and a cationic-like drug methylene blue (MB). Supported by a cationic polyelectrolyte (PAH), LbL films containing PAH/(CLP + MB) and PAH/(CLP + MB + AgNP) were grown up to 14 bilayers. The optical microscopy analysis revealed a decrease of the CLP vesicle sizes in the presence of MB as a possible consequence of the MB action onto the mechanical properties of the CLP membrane. From FTIR spectra, changes mainly related to peak position and band intensity and shape were observed in the spectra from PAH/CLP when in the presence of MB. The latter supports that the interactions between the phosphate and amine charged groups from CLP and PAH, respectively, established during the LbL film fabrication, besides the CLP hydrocarbon environment, are influenced by the presence of MB. Using the micro-Raman technique, a chemical mapping was build based on MB spectrum by resonance Raman scattering (RRS) and surface-enhanced resonance Raman scattering (SERRS). The later phenomenon was activated by Ag nanoparticles (AgNPs) trapped within the LbL film allowing collecting spectra for a single bilayer of PAH/(CLP + MB + AgNP). A rough estimation showed a SERRS amplification of 10(3) in comparison to RRS spectra. As a complementary approach, Langmuir films of CLP in the presence of co-spread MB were investigated through surface pressure vs mean molecular area (pi-A) isotherms. The results showed that for concentrations of MB below 100 mol%, the drug is expelled to water subphase for high values of surface pressure (condensed phase). For concentration at 100% and higher, the MB keeps bound to CLP floating monolayer. (C) 2010 Elsevier B.V. All rights reserved.

Spray layer-by-layer films based on phospholipid vesicles aiming sensing application via e-tongue system

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

Fault Current Limiter Using YBCO Coated Conductor-The Limiting Factor and Its Recovery Time

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

Fault section estimation in electric power systems using an optimization immune algorithm

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

Sliding mode for detection and accommodation of computation time delay fault

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

Higher prevalence of obsessive-compulsive spectrum disorders in rheumatic fever

Objective: This study aims to compare the prevalence of obsessive-compulsive spectrum disorders (OCSD) in psychiatric outpatients with and without a history of rheumatic fever (RF).Methods: An analytical cross-sectional study assessing a large sample of consecutive psychiatric outpatients at a Brazilian private practice was conducted during a 10-year period. Psychiatric diagnoses were made by a senior psychiatrist based on Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition. Best-estimate diagnosis procedure was also performed.Results: The total sample comprised 678 subjects, 13 of whom (1.92%) presented with a previous history of RF. This group showed a higher prevalence of subclinical obsessive-compulsive disorder (P=.025) and OCSD (P=.007) when compared to individuals with no such history.Conclusions: A previous history of RF was associated with OCSD. These results suggest that clinicians should be encouraged to actively investigate obsessive-compulsive symptoms and related disorders in patients with a positive history of RF. (C) 2009 Published by Elsevier B.V.