Paraconsistent Autonomous Mobile Robot Emmy III

This work presents some improvements regarding to the autonomous mobile robot Emmy based on Paraconsistent Annotated Evidential Logic ET. A discussion on navigation system is presented.

Economic and technical feasibility study of a combined-cycle cogeneration system associated with cellulose plants

In this paper, is presented an economical and technical feasibility study of a combined cycle cogeneration system proposed to be used in a pulp plant located in Brazil, where around 95% of country's pulp production is done by the use of Kraft Process. This process allows the use of black liquor and other by-products as fuel. This study is based upon actual data from a pulp plant with a daily production of 1000 tons., that generates part of the energy demanded by the process in a conventional cogeneration system with condensing steam turbine and two extractions. The addition of a gas turbine was studied to compare electricity production level and its related costs between original system and the new one, considering that the former can use industrial by-products and firewood as fuel, when required. Several parameters related to electric generation systems operation and production costs were studied. The use of natural gas in the combined cycle, in comparison with the use of firewood in the conventional system was studied. The advantages of natural gas fuel are highlighted. The surplus availability and the electricity generation costs are presented as a function of pulp and black liquor production.

Performance of constructed wetland system for public water supply

The project is being conducted in the town of Analândia, São Paulo, Brazil. The constructed wetlands system for water supply consists of a channel with floating aquatic macrophytes, HDS system (Water Decontamination with Soil - Patent PI 850.3030), chlorinating system, filtering system and distribution. The project objectives include investigating the process variables to further optimize design and operation factors, evaluating the relation of nutrients and plants development, biomass production, shoot development, nutrient cycling and total and fecal coliforms removal, comparing the treatment efficiency among the seasons of the year; and moreover to compare the average values obtained between February and June 1998 (Salati et al., 1998) with the average obtained for the same parameters between March and June 2000. Studies have been developed in order to verify during one year the drinking quality of the water for the following parameters: turbidity, color, pH, dissolved oxygen, total of dissolved solids, COD, chloride, among others, according to the Ministry of Health's Regulation 36. This system of water supply projected to treat 15 L s-1 has been in continuous operation for 2 years, it was implemented with support of the National Environment Fund (FNMA), administered by the Center of Environmental Studies (CEA-UNESP), while the technical supervision and design were performed by the Institute of Applied Ecology. The actual research project is being supported by FAPESP.

PMUs optimized allocation using a tabu search algorithm for fault location in electric power distribution system

Phasor Measurement Units (PMUs) optimized allocation allows control, monitoring and accurate operation of electric power distribution systems, improving reliability and service quality. Good quality and considerable results are obtained for transmission systems using fault location techniques based on voltage measurements. Based on these techniques and performing PMUs optimized allocation it is possible to develop an electric power distribution system fault locator, which provides accurate results. The PMUs allocation problem presents combinatorial features related to devices number that can be allocated, and also probably places for allocation. Tabu search algorithm is the proposed technique to carry out PMUs allocation. This technique applied in a 141 buses real-life distribution urban feeder improved significantly the fault location results. © 2004 IEEE.

An evaporative and desiccant cooling system for air conditioning in humid climates

Evaporative cooling operates using water and air as working fluids. It consists in water evaporation, through the passage of an airflow, thus decreasing the air temperature. This system has a great potential to provide thermal comfort in places where air humidity is low, being, however, less efficient where air humidity is high. A way to solve this problem is to use dehumidifiers to pre-conditioning the process air. This paper presents a system that can be used in humid climates coupling desiccant dehumidification equipment to evaporative coolers. The paper shows, initially, the main characteristics of the evaporative cooling and of the adsorption dehumidification systems. Later on the coupled systems, in which occurs a dehumidification by adsorption in a counter flow rotary heat exchanger following the evaporate cooling of the air in evaporative coolers, are analyzed. The thermodynamic equations of state are also presented. Following, this paper analyzes some operation parameters such as: reactivation temperature, R/P relationship (reactivation air flow/ process air flow) and the thermodynamic conditions of the entering air flow. The paper shows the conditions for the best operation point, with regard to thermal comfort conditions and to the energy used in the process. In addition this paper presents an application of the system in different climate characteristics of several tropical and equatorial cities. Copyright © 2005 by ABCM.

A low cost structured light system

The aim of this paper is to present the current development status of a low cost system for surface reconstruction with structured light. The acquisition system is composed of a single off-the-shelf digital camera and a pattern projector. A pattern codification strategy was developed to allow the pattern recognition automatically and a calibration methodology ensures the determination of the direction vector of each pattern. The experiments indicated that an accuracy of 0.5mm in depth could be achieved for typical applications.

Identification of structural damage in flexible structures using system norm and neural networks

Nowadays there is great interest in damage identification using non destructive tests. Predictive maintenance is one of the most important techniques that are based on analysis of vibrations and it consists basically of monitoring the condition of structures or machines. A complete procedure should be able to detect the damage, to foresee the probable time of occurrence and to diagnosis the type of fault in order to plan the maintenance operation in a convenient form and occasion. In practical problems, it is frequent the necessity of getting the solution of non linear equations. These processes have been studied for a long time due to its great utility. Among the methods, there are different approaches, as for instance numerical methods (classic), intelligent methods (artificial neural networks), evolutions methods (genetic algorithms), and others. The characterization of damages, for better agreement, can be classified by levels. A new one uses seven levels of classification: detect the existence of the damage; detect and locate the damage; detect, locate and quantify the damages; predict the equipment's working life; auto-diagnoses; control for auto structural repair; and system of simultaneous control and monitoring. The neural networks are computational models or systems for information processing that, in a general way, can be thought as a device black box that accepts an input and produces an output. Artificial neural nets (ANN) are based on the biological neural nets and possess habilities for identification of functions and classification of standards. In this paper a methodology for structural damages location is presented. This procedure can be divided on two phases. The first one uses norms of systems to localize the damage positions. The second one uses ANN to quantify the severity of the damage. The paper concludes with a numerical application in a beam like structure with five cases of structural damages with different levels of severities. The results show the applicability of the presented methodology. A great advantage is the possibility of to apply this approach for identification of simultaneous damages.

JSEG-based image segmentation in computer vision for agricultural mobile robot navigation

This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained.

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.

Optimized dynamic response of parallel operation of two single phase inverters based on evolutionary theory

In this work it is proposed an optimized dynamic response of parallel operation of two single-phase inverters with no control communication. The optimization aims the tuning of the slopes of P-ω and Q-V curves so that the system is stable, damped and minimum settling time. The slopes are tuned using an algorithm based on evolutionary theory. Simulation and experimental results are presented to prove the feasibility of the proposed approach. © 2010 IEEE.

ANN statistical image recognition method for computer vision in agricultural mobile robot navigation

The main application area in this project, is to deploy image processing and segmentation techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. Thereby, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for image recognition. Hence, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave computational platforms, along with the application of customized Back-propagation Multilayer Perceptron (MLP) algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of segmented images in which reasonably accurate results were obtained. © 2010 IEEE.

Performance and operation of the CMS electromagnetic calorimeter

The operation and general performance of the CMS electromagnetic calorimeter using cosmic-ray muons are described. These muons were recorded after the closure of the CMS detector in late 2008. The calorimeter is made of lead tungstate crystals and the overall status of the 75 848 channels corresponding to the barrel and endcap detectors is reported. The stability of crucial operational parameters, such as high voltage, temperature and electronic noise, is summarised and the performance of the light monitoring system is presented. © 2010 IOP Publishing Ltd and SISSA.

Pattern recognition structured heuristics methods for image processing in mobile robot navigation

In this project, the main focus is to apply image processing techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained. ©2010 IEEE.

A multi-objective programming approach for the optimal operation of distributed generation considering uncertainty

Due to the renewed interest in distributed generation (DG), the number of DG units incorporated in distribution systems has been rapidly increasing in the past few years. This situation requires new analysis tools for understanding system performance, and taking advantage of the potential benefits of DG. This paper presents an evolutionary multi-objective programming approach to determine the optimal operation of DG in distribution systems. The objectives are the minimization of the system power losses and operation cost of the DG units. The proposed approach also considers the inherent stochasticity of DG technologies powered by renewable resources. Some tests were carried out on the IEEE 34 bus distribution test system showing the robustness and applicability of the proposed methodology. © 2011 IEEE.

Use of myoelectric signals to command mobile entertainment robot by disabled children: Design and control architecture

Severely disabled children have little chance of environmental and social exploration and discovery. This lack of interaction and independency may lead to an idea that they are unable to do anything by themselves. In an attempt to help children in this situation, educational robotics can offer and aid, once it can provide them a certain degree of independency in the exploration of environment. The system developed in this work allows the child to transmit the commands to a robot through myoelectric and movement sensors. The sensors are placed on the child's body so they can obtain information from the body inclination and muscle contraction, thus allowing commanding, through a wireless communication, the mobile entertainment robot to carry out tasks such as play with objects and draw. In this paper, the details of the robot design and control architecture are presented and discussed. With this system, disabled children get a better cognitive development and social interaction, balancing in a certain way, the negative effects of their disabilities. © 2012 IEEE.