52 resultados para smart transducer

em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"


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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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IEEE 1451 Standard is intended to address the smart transducer interfacing problematic in network environments. Usually, proprietary hardware and software is a very efficient solution to in planent the IEEE 1451 normative, although can be expensive and inflexible. In contrast, the use of open and standardized tools for implementing the IEEE 1451 normative is proposed in this paper. Tools such as Java and Phyton programming languages, Linux, programmable logic technology, Personal Computer resources and Ethernet architecture were integrated in order to constructa network node based on the IEEE 1451 standards. The node can be applied in systems based on the client-server communication model The evaluation of the employed tools and expermental results are presented. © 2005 IEEE.

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This work presents the development of an IEEE 1451.2 protocol controller based on a low-cost FPGA that is directly connected to the parallel port of a conventional personal computer. In this manner it is possible to implement a Network Capable Application Processor (NCAP) based on a personal computer, without parallel port modifications. This approach allows supporting the ten signal lines of the 10-wire IEEE 1451.2 Transducer Independent Interface (TII), that connects the network processor to the Smart Transducer Interface Module (STIM) also defined in the IEEE 1451.2 standard. The protocol controller is connected to the STIM through the TII's physical interface, enabling the portability of the application at the transducer and network processor level. The protocol controller architecture was fully developed in VHDL language and we have projected a special prototype configured in a general-purpose programmable logic device. We have implemented two versions of the protocol controller, which is based on IEEE 1451 standard, and we have obtained results using simulation and experimental tests. (c) 2008 Elsevier B.V. All rights reserved.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Pós-graduação em Engenharia Elétrica - FEIS

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

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Lignins extracted from sugar cane bagasse using different alcohols in the organosolv-CO(2) supercritical pulping process have been applied in the fabrication of ultrathin films through the Langmuir-Blodgett technique. Langmuir films were characterized by surface pressure versus mean molecular area (Pi-A) isotherms to exploit the sensitivity of nanostructured lignin films to metallic ions (Cu(2+), Cd(2+) and Pb(2+)). The Pi-A isotherms were shifted to larger molecular areas when heavy metal ions are present into the subphase, which might be related to electrostatic repulsions between metallic ions entrapped within the lignin molecular structure. Taking the advantage of metal incorporation, Langmuir monolayers were transferred onto solid substrates forming Langmuir-Blodgett (LB) films to be used as a transducer in an "electronic tongue" system to detect Cu(2+) in aqueous solution below threshold standard established by the Brazilian regulation. Both techniques impedance spectroscopy and electrochemistry have been used in these experiments. Complementary, Fourier transform infrared (FTIR) spectroscopy recorded for LB films before and after soaking into Cu(2+) aqueous solution revealed an interaction between the lignin phenyl groups and the metallic ion. (C) 2007 Elsevier B.V.. All rights reserved.

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

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During pregnancy, the maternal endocrine pancreas undergoes, as a consequence of placental lactogens and prolactin (PR,L) action, functional changes that are characterized by increased glucose-induced insulin secretion. After delivery, the maternal endocrine pancreas rapidly returns to nonpregnant state, which is mainly attributed to the increased serum levels of glucocorticoids (GCs). Although GCs are known to decrease insulin secretion and counteract PRL action, the mechanisms for these effects are poorly understood. We have previously demonstrated that signal transducer and activator of transcription 3 (STAT3) is increased in islets treated with PRL. In the present study, we show that STAT3 expression and serine phosphorylation are increased in pancreatic islets at the end of pregnancy (P19). STAT3 serine phosphorylation rapidly returned to basal levels 3 days after delivery (U). The expression of the sarcoendoplasmic reticulum Ca2+-ATPase 2 (SERCA2), a crucial protein involved in the regulation of calcium handling in P-cells, was also increased in P19, returning to basal levels at L3. PRL increased SERCA2 and STAT3 expressions and STAT3 serine phosphorylation in RINm5F cells. The upregulation of SERCA2 by PRL was abolished after STAT3 knockdown. Moreover, PRL-induced STAT3 serine phosphorylation and SERCA2 expression were inhibited by dexamethasone (DEX). Insulin secretion from islets of PI 9 rats pre-incubated with thapsigargin and L3 rats showed a dramatic suppression of first phase of insulin release. The present results indicate that PRL regulates SERCA2 expression by a STAT3-dependent mechanism. PRL effect is counteracted by DEX and might contribute to the adaptation of maternal endocrine pancreas during the peripartum period.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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This paper presents a non-model based technique to detect, locate, and characterize structural damage by combining the impedance-based structural health monitoring technique with an artificial neural network. The impedance-based structural health monitoring technique, which utilizes the electromechanical coupling property of piezoelectric materials, has shown engineering feasibility in a variety of practical field applications. Relying on high frequency structural excitations (typically>30 kHz), this technique is very sensitive to minor structural changes in the near field of the piezoelectric sensors. In order to quantitatively assess the state of structures, two sets of artificial neural networks, which utilize measured electrical impedance signals for input patterns, were developed. By employing high frequency ranges and by incorporating neural network features, this technique is able to detect the damage in its early stage and to estimate the nature of damage without prior knowledge of the model of structures. The paper concludes with an experimental example, an investigation on a massive quarter scale model of a steel bridge section, in order to verify the performance of this proposed methodology.

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Smart material technology has become an area of increasing interest for the development of lighter and stronger structures which are able to incorporate actuator and sensor capabilities for collocated control. In the design of actively controlled structures, the determination of the actuator locations and the controller gains, is a very important issue. For that purpose, smart material modelling, modal analysis methods, control and optimization techniques are the most important ingredients to be taken into account. The optimization problem to be solved in this context presents two interdependent aspects. The first one is related to the discrete optimal actuator location selection problem which is solved in this paper using genetic algorithms. The second is represented by a continuous variable optimization problem, through which the control gains are determined using classical techniques. A cantilever Euler-Bernoulli beam is used to illustrate the presented methodology.