Sistema especialista para detecção de falhas em comandos elétricos

This work consists of the creation of a Specialist System which utilizes production rules to detect inadequacies in the command circuits of an operation system and commands of electric engines known as Direct Start. Jointly, three other modules are developed: one for the simulation of the commands diagram, one for the simulation of faults and another one for the correction of defects in the diagram, with the objective of making it possible to train the professionals aiming a better qualification for the operation and maintenance. The development is carried through in such a way that the structure of the task allows the extending of the system and a succeeding promotion of other bigger and more complex typical systems. The computational environment LabView is employed to enable the system

Identificação de modelos polinomiais narx utilizando algoritmos combinados de detecção de estrutura e estimação de parâmetros com aplicações práticas

A modelagem de processos industriais tem auxiliado na produção e minimização de custos, permitindo a previsão dos comportamentos futuros do sistema, supervisão de processos e projeto de controladores. Ao observar os benefícios proporcionados pela modelagem, objetiva-se primeiramente, nesta dissertação, apresentar uma metodologia de identificação de modelos não-lineares com estrutura NARX, a partir da implementação de algoritmos combinados de detecção de estrutura e estimação de parâmetros. Inicialmente, será ressaltada a importância da identificação de sistemas na otimização de processos industriais, especificamente a escolha do modelo para representar adequadamente as dinâmicas do sistema. Em seguida, será apresentada uma breve revisão das etapas que compõem a identificação de sistemas. Na sequência, serão apresentados os métodos fundamentais para detecção de estrutura (Modificado Gram- Schmidt) e estimação de parâmetros (Método dos Mínimos Quadrados e Método dos Mínimos Quadrados Estendido) de modelos. No trabalho será também realizada, através dos algoritmos implementados, a identificação de dois processos industriais distintos representados por uma planta de nível didática, que possibilita o controle de nível e vazão, e uma planta de processamento primário de petróleo simulada, que tem como objetivo representar um tratamento primário do petróleo que ocorre em plataformas petrolíferas. A dissertação é finalizada com uma avaliação dos desempenhos dos modelos obtidos, quando comparados com o sistema. A partir desta avaliação, será possível observar se os modelos identificados são capazes de representar as características estáticas e dinâmicas dos sistemas apresentados nesta dissertação

Estratégia de controle robusto para interconexão de sistemas PV trifásicos à rede elétrica

Atualmente há uma grande preocupação em relação a substituição das fontes não renováveis pelas fontes renováveis na geração de energia elétrica. Isto ocorre devido a limitação do modelo tradicional e da crescente demanda. Com o desenvolvimento dos conversores de potência e a eficácia dos esquemas de controle, as fontes renováveis têm sido interligadas na rede elétrica, em um modelo de geração distribuída. Neste sentido, este trabalho apresenta uma estratégia de controle não convencional, com a utilização de um controlador robusto, para a interconexão de sistemas fotovoltaicos com à rede elétrica trifásica. A compensação da qualidade de energia no ponto de acoplamento comum (PAC) é realizada pela estratégia proposta. As técnicas tradicionais utilizam detecção de harmônicos, já neste trabalho o controle das correntes é feita de uma forma indireta sem a necessidade desta detecção. Na estratégia indireta é de grande importância que o controle da tensão do barramento CC seja efetuado de uma forma que não haja grandes flutuações, e que a banda passante do controlador em regime permanente seja baixa para que as correntes da rede não tenham um alto THD. Por este motivo é utilizado um controlador em modo dual DSM-PI, que durante o transitório se comporta como um controlador em modo deslizante SM-PI, e em regime se comporta como um PI convencional. A corrente é alinhada ao ângulo de fase do vetor tensão da rede elétrica, obtido a partir do uso de um PLL. Esta aproximação permite regular o fluxo de potência ativa, juntamente com a compensação dos harmônicos e também promover a correção do fator de potência no ponto de acoplamento comum. Para o controle das correntes é usado um controlador dupla sequencia, que utiliza o princípio do modelo interno. Resultados de simulação são apresentados para demonstrar a eficácia do sistema de controle proposto

Sistema inteligente para detecção de manchas de óleo na superfície marinha através de imagens de SAR

Oil spill on the sea, accidental or not, generates enormous negative consequences for the affected area. The damages are ambient and economic, mainly with the proximity of these spots of preservation areas and/or coastal zones. The development of automatic techniques for identification of oil spots on the sea surface, captured through Radar images, assist in a complete monitoring of the oceans and seas. However spots of different origins can be visualized in this type of imaging, which is a very difficult task. The system proposed in this work, based on techniques of digital image processing and artificial neural network, has the objective to identify the analyzed spot and to discern between oil and other generating phenomena of spot. Tests in functional blocks that compose the proposed system allow the implementation of different algorithms, as well as its detailed and prompt analysis. The algorithms of digital image processing (speckle filtering and gradient), as well as classifier algorithms (Multilayer Perceptron, Radial Basis Function, Support Vector Machine and Committe Machine) are presented and commented.The final performance of the system, with different kind of classifiers, is presented by ROC curve. The true positive rates are considered agreed with the literature about oil slick detection through SAR images presents

Compressão Seletiva de Imagens Coloridas com Detecção Automática de Regiões de Interesse

There has been an increasing tendency on the use of selective image compression, since several applications make use of digital images and the loss of information in certain regions is not allowed in some cases. However, there are applications in which these images are captured and stored automatically making it impossible to the user to select the regions of interest to be compressed in a lossless manner. A possible solution for this matter would be the automatic selection of these regions, a very difficult problem to solve in general cases. Nevertheless, it is possible to use intelligent techniques to detect these regions in specific cases. This work proposes a selective color image compression method in which regions of interest, previously chosen, are compressed in a lossless manner. This method uses the wavelet transform to decorrelate the pixels of the image, competitive neural network to make a vectorial quantization, mathematical morphology, and Huffman adaptive coding. There are two options for automatic detection in addition to the manual one: a method of texture segmentation, in which the highest frequency texture is selected to be the region of interest, and a new face detection method where the region of the face will be lossless compressed. The results show that both can be successfully used with the compression method, giving the map of the region of interest as an input

Indicadores de cálcio e de voltagem codificados geneticamente na detecção de potenciais de ação e inputs sinápticos em cultura de neurônios hipocampais

Recently, genetically encoded optical indicators have emerged as noninvasive tools of high spatial and temporal resolution utilized to monitor the activity of individual neurons and specific neuronal populations. The increasing number of new optogenetic indicators, together with the absence of comparisons under identical conditions, has generated difficulty in choosing the most appropriate protein, depending on the experimental design. Therefore, the purpose of our study was to compare three recently developed reporter proteins: the calcium indicators GCaMP3 and R-GECO1, and the voltage indicator VSFP butterfly1.2. These probes were expressed in hippocampal neurons in culture, which were subjected to patchclamp recordings and optical imaging. The three groups (each one expressing a protein) exhibited similar values of membrane potential (in mV, GCaMP3: -56 ±8.0, R-GECO1: -57 ±2.5; VSFP: -60 ±3.9, p = 0.86); however, the group of neurons expressing VSFP showed a lower average of input resistance than the other groups (in Mohms, GCaMP3: 161 ±18.3; GECO1-R: 128 ±15.3; VSFP: 94 ±14.0, p = 0.02). Each neuron was submitted to current injections at different frequencies (10 Hz, 5 Hz, 3 Hz, 1.5 Hz, and 0.7 Hz) and their fluorescence responses were recorded in time. In our study, only 26.7% (4/15) of the neurons expressing VSFP showed detectable fluorescence signal in response to action potentials (APs). The average signal-to-noise ratio (SNR) obtained in response to five spikes (at 10 Hz) was small (1.3 ± 0.21), however the rapid kinetics of the VSFP allowed discrimination of APs as individual peaks, with detection of 53% of the evoked APs. Frequencies below 5 Hz and subthreshold signals were undetectable due to high noise. On the other hand, calcium indicators showed the greatest change in fluorescence following the same protocol (five APs at 10 Hz). Among the GCaMP3 expressing neurons, 80% (8/10) exhibited signal, with an average SNR value of 21 ±6.69 (soma), while for the R-GECO1 neurons, 50% (2/4) of the neurons had signal, with a mean SNR value of 52 ±19.7 (soma). For protocols at 10 Hz, 54% of the evoked APs were detected with GCaMP3 and 85% with R-GECO1. APs were detectable in all the analyzed frequencies and fluorescence signals were detected from subthreshold depolarizations as well. Because GCaMP3 is the most likely to yield fluorescence signal and with high SNR, some experiments were performed only with this probe. We demonstrate that GCaMP3 is effective in detecting synaptic inputs (involving Ca2+ influx), with high spatial and temporal resolution. Differences were also observed between the SNR values resulting from evoked APs, compared to spontaneous APs. In recordings of groups of cells, GCaMP3 showed clear discrimination between activated and silent cells, and reveals itself as a potential tool in studies of neuronal synchronization. Thus, our results indicate that the presently available calcium indicators allow detailed studies on neuronal communication, ranging from individual dendritic spines to the investigation of events of synchrony in neuronal networks genetically defined. In contrast, studies employing VSFPs represent a promising technology for monitoring neural activity and, although still to be improved, they may become more appropriate than calcium indicators, since neurons work on a time scale faster than events of calcium may foresee

CrossMDA2: Uma abordagem para minimizar o problema da fragilidade de pointcuts na evolução de sistemas orientados a aspectos

This work proposes a model based approach for pointcut management in the presence of evolution in aspect oriented systems. The proposed approach, called conceptual visions based pointcuts, is motivated by the observation of the shortcomings in traditional approaches pointcuts definition, which generally refer directly to software structure and/or behavior, thereby creating a strong coupling between pointcut definition and the base code. This coupling causes the problem known as pointcut fragility problem and hinders the evolution of aspect-oriented systems. This problem occurs when all the pointcuts of each aspect should be reviewed due to any software changes/evolution, to ensure that they remain valid even after the changes made in the software. Our approach is focused on the pointcuts definition based on a conceptual model, which has definitions of the system's structure in a more abstract level. The conceptual model consists of classifications (called conceptual views) on entities of the business model elements based on common characteristics, and relationships between these views. Thus the pointcuts definitions are created based on the conceptual model rather than directly referencing the base model. Moreover, the conceptual model contains a set of relationships that allows it to be automatically verified if the classifications in the conceptual model remain valid even after a software change. To this end, all the development using the conceptual views based pointcuts approach is supported by a conceptual framework called CrossMDA2 and a development process based on MDA, both also proposed in this work. As proof of concept, we present two versions of a case study, setting up a scenario of evolution that shows how the use of conceptual visions based pointcuts helps detecting and minimizing the pointcuts fragility. For the proposal evaluation the Goal/Question/Metric (GQM) technique is used together with metrics for efficiency analysis in the pointcuts definition

Detecção e recuperação de falhas para a máquina de redução de grafos PEWS-AM

Web services are software units that allow access to one or more resources, supporting the deployment of business processes in the Web. They use well-defined interfaces, using web standard protocols, making possible the communication between entities implemented on different platforms. Due to these features, Web services can be integrated as services compositions to form more robust loose coupling applications. Web services are subject to failures, unwanted situations that may compromise the business process partially or completely. Failures can occur both in the design of compositions as in the execution of compositions. As a result, it is essential to create mechanisms to make the implementation of service compositions more robust and to treat failures. Specifically, we propose the support for fault recovery in service compositions described in PEWS language and executed on PEWS-AM, an graph reduction machine. To support recovery failure on PEWS-AM, we extend the PEWS language specification and adapted the rules of translation and reduction of graphs for this machine. These contributions were made both in the model of abstract machine as at the implementation level

Sistema de aquisição de dados para estudos de transiente de pressão e detecção de vazamentos em oleodutos

In February 2011, the National Agency of Petroleum, Natural Gas and Biofuels (ANP) has published a new Technical Rules for Handling Land Pipeline Petroleum and Natural Gas Derivatives (RTDT). Among other things, the RTDT made compulsory the use of monitoring systems and leak detection in all onshore pipelines in the country. This document provides a study on the method for detection of transient pressure. The study was conducted on a industrial duct 16" diameter and 9.8 km long. The pipeline is fully pressurized and carries a multiphase mixture of crude oil, water and natural gas. For the study, was built an infrastructure for data acquisition and validation of detection algorithms. The system was designed with SCADA architecture. Piezoresistive sensors were installed at the ends of the duct and Digital Signal Processors (DSPs) were used for sampling, storage and processing of data. The study was based on simulations of leaks through valves and search for patterns that characterize the occurrence of such phenomena

Contribuições para a detecção e identificação de faltas em inversores Multiníveis

This work presents contributions in the detection and identication of faults in multilevel inverters through the study of the converters behavior under these operation conditions. Basically, the approached fault consists of an open-circuit in any switch of a three-level clamped diode inverter. The converter operation is characterized in the pre and post-fault states. A wave form behavior analysis of the pole voltage, phase current and dc-bus current is also done, which highlights characteristics that allow the detection of failure and, even, under favorable conditions, the identication of the faulty device. A compensation strategy of the approached fault (open-switch) is also investigated with the purpose of maintaining the driving system operational when a failure occurs. The proposed topology uses SCRs in parallel with the internal switches of the inverter, which allows, in some occasions, the full utilization of the dc-bus

Detecção e diagnóstico de falhas não-supervisionados baseados em estimativa de densidade recursiva e classificador fuzzy auto-evolutivo

In this work, we propose a two-stage algorithm for real-time fault detection and identification of industrial plants. Our proposal is based on the analysis of selected features using recursive density estimation and a new evolving classifier algorithm. More specifically, the proposed approach for the detection stage is based on the concept of density in the data space, which is not the same as probability density function, but is a very useful measure for abnormality/outliers detection. This density can be expressed by a Cauchy function and can be calculated recursively, which makes it memory and computational power efficient and, therefore, suitable for on-line applications. The identification/diagnosis stage is based on a self-developing (evolving) fuzzy rule-based classifier system proposed in this work, called AutoClass. An important property of AutoClass is that it can start learning from scratch". Not only do the fuzzy rules not need to be prespecified, but neither do the number of classes for AutoClass (the number may grow, with new class labels being added by the on-line learning process), in a fully unsupervised manner. In the event that an initial rule base exists, AutoClass can evolve/develop it further based on the newly arrived faulty state data. In order to validate our proposal, we present experimental results from a level control didactic process, where control and error signals are used as features for the fault detection and identification systems, but the approach is generic and the number of features can be significant due to the computationally lean methodology, since covariance or more complex calculations, as well as storage of old data, are not required. The obtained results are significantly better than the traditional approaches used for comparison

Detecção de áreas degradadas na sub-bacia hidrográfica do rio taperoá/pb, utilizando parâmetros físicos dos sensores modis/terra e tm/landsat

This study includes the results of the analysis of areas susceptible to degradation by remote sensing in semi-arid region, which is a matter of concern and affects the whole population and the catalyst of this process occurs by the deforestation of the savanna and improper practices by the use of soil. The objective of this research is to use biophysical parameters of the MODIS / Terra and images TM/Landsat-5 to determine areas susceptible to degradation in semi-arid Paraiba. The study area is located in the central interior of Paraíba, in the sub-basin of the River Taperoá, with average annual rainfall below 400 mm and average annual temperature of 28 ° C. To draw up the map of vegetation were used TM/Landsat-5 images, specifically, the composition 5R4G3B colored, commonly used for mapping land use. This map was produced by unsupervised classification by maximum likelihood. The legend corresponds to the following targets: savanna vegetation sparse and dense, riparian vegetation and exposed soil. The biophysical parameters used in the MODIS were emissivity, albedo and vegetation index for NDVI (NDVI). The GIS computer programs used were Modis Reprojections Tools and System Information Processing Georeferenced (SPRING), which was set up and worked the bank of information from sensors MODIS and TM and ArcGIS software for making maps more customizable. Initially, we evaluated the behavior of the vegetation emissivity by adapting equation Bastiaanssen on NDVI for spatialize emissivity and observe changes during the year 2006. The albedo was used to view your percentage of increase in the periods December 2003 and 2004. The image sensor of Landsat TM were used for the month of December 2005, according to the availability of images and in periods of low emissivity. For these applications were made in language programs for GIS Algebraic Space (LEGAL), which is a routine programming SPRING, which allows you to perform various types of algebras of spatial data and maps. For the detection of areas susceptible to environmental degradation took into account the behavior of the emissivity of the savanna that showed seasonal coinciding with the rainy season, reaching a maximum emissivity in the months April to July and in the remaining months of a low emissivity . With the images of the albedo of December 2003 and 2004, it was verified the percentage increase, which allowed the generation of two distinct classes: areas with increased variation percentage of 1 to 11.6% and the percentage change in areas with less than 1 % albedo. It was then possible to generate the map of susceptibility to environmental degradation, with the intersection of the class of exposed soil with varying percentage of the albedo, resulting in classes susceptibility to environmental degradation

Potencialidades analíticas do dietilditiofosfato de amônio em espectrometria de massas com plasma indutivamente acoplado empregando extração em fase sólida e sistemas de injeção em fluxo

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Detecção de falhas em estruturas inteligentes usando otimização por nuvem de partículas: fundamentos e estudo de casos

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

Detecção de áreas de oclusão para geração de ortoimagem verdadeira utilizando dados LASER

Pós-graduação em Ciências Cartográficas - FCT