866 resultados para Monitoring Systems


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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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This work studies the capability of generalization of Neural Network using vibration based measurement data aiming at operating condition and health monitoring of mechanical systems. The procedure uses the backpropagation algorithm to classify the input patters of a system with different stiffness ratios. It has been investigated a large set of input data, containing various stiffness ratios as well as a reduced set containing only the extreme ones in order to study generalizing capability of the network. This allows to definition of Neural Networks capable to use a reduced set of data during the training phase. Once it is successfully trained, it could identify intermediate failure condition. Several conditions and intensities of damages have been studied by using numerical data. The Neural Network demonstrated a good capacity of generalization for all case. Finally, the proposal was tested with experimental data.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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This study aimed to evaluate laser fluorescence (LF) for monitoring the initial stage of subsurface de- and remineralization (<150 mu m depth). Ninety-six sound blocks of bovine enamel, selected according to surface hardness (SH) and LF were used in two experimental studies, in vitro and in situ. In vitro, blocks were exposed to a demineralizing solution, then remineralized by pH cycling for 6 days. In situ, 10 volunteers wore acrylic palatal appliances, each containing 4 dental enamel blocks that were demineralized for 14 days by exposure to 20% sucrose solution. Following this treatment, blocks were submitted to remineralization for 1 week with fluoride dentifrice (1,100 mu g F/g). In both experiments, SH and LH were measured after demineralization and after remineralization. Further, enamel blocks were selected after the demineralization/remineralization steps for measurement of cross-sectional hardness and integrated loss of subsurface hardness (Delta KHN). SH and Delta KHN showed significant differences among the phases in each study. LF values for sound, demineralized and remineralized enamel were: 5.2 +/- 1.1, 8.1 +/- 1.2 and 5.6 +/- 0.8, respectively, in the in vitro study, and 5.3 +/- 0.3, 16.5 +/- 4.7 and 6.5 +/- 2.5, respectively, in the in situ study, values for demineralized enamel being significantly higher than for sound and remineralized enamel in both studies. However, LF was correlated with Delta KHN only in situ. LF was capable of monitoring de- and remineralization in early lesions in situ, when bacteria are presumably present in the caries lesion body, but is not correlated with mineral changes in bacteria-free systems. Copyright (C) 2009 S. Karger AG, Basel

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

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An electronic ballast for multiple tubular fluorescent lamp systems is presented. The proposed structure has a high value for the power factor, a dimming capability, and soft switching of the semiconductor devices operated at high frequencies. A zero-current switching pulse width modulated SEPIC converter is used as the rectifying stage and it is controlled using the instantaneous average input current technique. The inverting stage consists of classical resonant half-bridge converter with series-resonant parallel-loaded filters. The dimming control technique is based on varying the switching frequency and monitoring the phase shift of the current drained by the filters and lamps in order to establish a closed loop control. Experimental results are presented that validate the theoretical analysis.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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This paper describes an urban traffic control system which aims at contributing to a more efficient traffic management system in the cities of Brazil. It uses fuzzy sets, case-based reasoning, and genetic algorithms to handle dynamic and unpredictable traffic scenarios, as well as uncertain, incomplete, and inconsistent information. The system is composed by one supervisor and several controller agents, which cooperate with each other to improve the system's results through Artificial Intelligence Techniques.

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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, multiple 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 experimental examples, investigations on a massive quarter scale model of a steel bridge section and a space truss structure, in order to verify the performance of this proposed methodology.

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This work involved the development of a smart system dedicated to surface burning detection in the grinding process through constant monitoring of the process by acoustic emission and electrical power signals. A program in Visual Basic® for Windows® was developed, which collects the signals through an analog-digital converter and further processes them using burning detection algorithms already known. Three other parameters are proposed here and a comparative study carried out. When burning occurs, the newly developed software program sends a control signal warning the operator or interrupting the process, and delivers process information via the Internet. Parallel to this, the user can also interfere in the process via Internet, changing parameters and/or monitoring the grinding process. The findings of a comparative study of the various parameters are also discussed here. Copyright © 2006 by ABCM.

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The assessment of welfare issues has been a challenge for poultry producers, and lately welfare standards needs to be reached in order to agree with international market demand. This research proposes the use of continuous behavior monitoring in order to contribute for assessing welfare. A software was developed using the language Clarium. The software managed the recording of data as well as the data searching in the database Firebird. Both software and the observational methodology were tested in a trial conducted inside an environmental chamber, using three genetics of broiler breeders. Behavioral pattern was recorded and correlated to ambient thermal and aerial variation. Monitoring video cameras were placed on the roof facing the used for registering the bird's behavior. From video camera images were recorded during the total period when the ambient was bright, and for analyzing the video images a sample of 15min observation in the morning and 15 min in the afternoon was used, adding up to 30 min daily observation. A specific model so-called behavior was developed inside the software for counting specific behavior and its frequency of occurrence, as well as its duration. Electronic identification was recorded for 24h period. Behavioral video recording images was related to the data recorded using electronic identification.. Statistical analysis of data allowed to identify behavioral differences related to the change in thermal environment, and ultimately indicating thermal stress and departure from welfare conditions.

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This paper presents the virtual environment implementation for project simulation and conception of supervision and control systems for mobile robots, that are capable to operate and adapting in different environments and conditions. This virtual system has as purpose to facilitate the development of embedded architecture systems, emphasizing the implementation of tools that allow the simulation of the kinematic conditions, dynamic and control, with real time monitoring of all important system points. For this, an open control architecture is proposal, integrating the two main techniques of robotic control implementation in the hardware level: systems microprocessors and reconfigurable hardware devices. The implemented simulator system is composed of a trajectory generating module, a kinematic and dynamic simulator module and of a analysis module of results and errors. All the kinematic and dynamic results shown during the simulation can be evaluated and visualized in graphs and tables formats, in the results analysis module, allowing an improvement in the system, minimizing the errors with the necessary adjustments optimization. For controller implementation in the embedded system, it uses the rapid prototyping, that is the technology that allows, in set with the virtual simulation environment, the development of a controller project for mobile robots. The validation and tests had been accomplish with nonholonomics mobile robots models with diferencial transmission. © 2008 IEEE.

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The structural health monitoring (SHM) systems based on electromechanical (E/M) impedance technique have been widely investigated. Although many studies indicate the reliability of this technique, some practical considerations still have to be considered in real applications. This paper presents an experimental analysis of the effect of the structure area on the system's performance. The results indicate that the sensitivity of the system to detect damage decreases significantly when the host structure has large cross-section area. Copyright © 2009 by ASME.