Fault Detection And Classification
Mostrando 1-9 de 9 artigos, teses e dissertações.
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1. Modelagem nebulosa evolutiva: novas topologias e algoritmos de aprendizagem
This works aims to introduce new evolving fuzzy topologies and learning algorithms. Evolving fuzzy systems are defined as new class of intelligent fuzzy systems, with a high flexibility and autonomy. These systems are able to address problems like nonlinear system identification, control and pattern classification in a dynamic changing environment, adapting
Publicado em: 2011
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2. Estudo e implementação de algoritmos inteligentes para detecção e classificação de falhas na medição de gás natural / Estudo e implementação de algoritmos inteligentes para detecção e classificação de falhas na medição de gás natural
This master dissertation presents the study and implementation of inteligent algorithms to monitor the measurement of sensors involved in natural gas custody transfer processes. To create these algoritmhs Artificial Neural Networks are investigated because they have some particular properties, such as: learning, adaptation, prediction. A neural predictor is
Publicado em: 2009
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3. Electrical system fault based on the resulting magnetic signature by Wavelet. / Análise da assinatura magnética resultante de faltas em sistemas elétricos via wavelets.
A methodology based on the analysis of magnetic fields for monitoring the quality of energy in electrical systems is presented herein. Aspects referring to fault detection in electrical systems in particular are evaluated. Contrary to the traditional monitoring process, in which sensors must be physically linked to the circuits under analysis, the results ar
Publicado em: 2009
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4. Detecção e isolamento de falhas em sistemas dinâmicos baseados em redes neurais
This master dissertation presents the development of a fault detection and isolation system based in neural network. The system is composed of two parts: an identification subsystem and a classification subsystem. Both of the subsystems use neural network techniques with multilayer perceptron training algorithm. Two approaches for identifica-tion sta
Publicado em: 2007
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5. Detecção e diagnóstico de falhas em motores de indução
This main purpose of this work is to design and implement a system to detect and diagnose electrical faults (stator inter-turn short circuit and broken rotor bars) and mechanical faults (unbalance and shaft misalignments) for three phase induction machines. This approach starts by obtaining the best patterns for fault detection and symmetrical models for the
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 08/07/2005
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6. Neural networks forecasting and classification-based techniques for novelty detection in time series
Novelty detection can be defined as the identification of new or unknown data that a machine learning system is not aware during training. Novelty detection algorithms are designed to classify input patterns as normal or novelty. These algorithms are used in several areas such as computer vision, machine fault detection, network security and fraud detection.
Publicado em: 2004
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7. Wavelet-based techniques for adaptive feature extraction and pattern recognition.
In this work, wavelet-based techniques are studxied for adaptive feature extraction in the time-frequency plane. Emphasis is placed on pattern recognition problems, in particular fault detection in control systems and classification / clustering electrocardiographic signals. In the context of fault detection, a technique for residue generation using wavelet
Publicado em: 1999
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8. Estrategias de detecção e diagnostico de falhas em sistemas dinamicos
Analytical redundancy for fault detection and diagnosis of dynamic systems, FDD, has been approached by several methodologies, state estimation, parameter estimation, expert systems, and pattern classification and recognition being typical examples. In particular, pattern classification and recognition methods adopt probabilistic, heuristic, neural, and fuzz
Publicado em: 1997
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9. SISTEMA HÍBRIDO DE APOIO À DECISÃO PARA DETECCÇÃO E DIAGNÓSTICO DE FALHAS EM REDES ELÉTRICAS / HYBRID DECISION SUPPORT SYSTEM FOR DETECTION AND DIAGNOSIS OF FAULTS IN ELECTRICAL NETWORKS
This work examines the application of hybrid systems based on Artificial Neural Networks (ANN) and Expert Systems (ES) in detecting and diagnosing faults in Electrical Systems. The research consists of three main parts: the study of cases. In the study of problem, was examined, the importance of detecting and diagnosing faults in Electrical Systems concentra
Publicado em: 1997