Implementação de um Módulo de Supervisão para um Sistema de Detecção de Vazamentos em Dutos de Petróleo

The transport of fluids through pipes is used in the oil industry, being the pipelines an important link in the logistics flow of fluids. However, the pipelines suffer deterioration in their walls caused by several factors which may cause loss of fluids to the environment, justifying the investment in techniques and methods of leak detection to minimize fluid loss and environmental damage. This work presents the development of a supervisory module in order to inform to the operator the leakage in the pipeline monitored in the shortest time possible, in order that the operator log procedure that entails the end of the leak. This module is a component of a system designed to detect leaks in oil pipelines using sonic technology, wavelets and neural networks. The plant used in the development and testing of the module presented here was the system of tanks of LAMP, and its LAN, as monitoring network. The proposal consists of, basically, two stages. Initially, assess the performance of the communication infrastructure of the supervisory module. Later, simulate leaks so that the DSP sends information to the supervisory performs the calculation of the location of leaks and indicate to which sensor the leak is closer, and using the system of tanks of LAMP, capture the pressure in the pipeline monitored by piezoresistive sensors, this information being processed by the DSP and sent to the supervisory to be presented to the user in real time

Implementação de um Módulo de Supervisão para um Sistema de Detecção de Vazamentos em Dutos de Petróleo

The transport of fluids through pipes is used in the oil industry, being the pipelines an important link in the logistics flow of fluids. However, the pipelines suffer deterioration in their walls caused by several factors which may cause loss of fluids to the environment, justifying the investment in techniques and methods of leak detection to minimize fluid loss and environmental damage. This work presents the development of a supervisory module in order to inform to the operator the leakage in the pipeline monitored in the shortest time possible, in order that the operator log procedure that entails the end of the leak. This module is a component of a system designed to detect leaks in oil pipelines using sonic technology, wavelets and neural networks. The plant used in the development and testing of the module presented here was the system of tanks of LAMP, and its LAN, as monitoring network. The proposal consists of, basically, two stages. Initially, assess the performance of the communication infrastructure of the supervisory module. Later, simulate leaks so that the DSP sends information to the supervisory performs the calculation of the location of leaks and indicate to which sensor the leak is closer, and using the system of tanks of LAMP, capture the pressure in the pipeline monitored by piezoresistive sensors, this information being processed by the DSP and sent to the supervisory to be presented to the user in real time

Implantação de um sistema de detecção de vazamentos em oleodutos com tratamento de alarmes falsos

The pumping of fluids in pipelines is the most economic and safe form of transporting fluids. That explains why in Europe there was in 1999 about 30.000 Km [7] of pipelines of several diameters, transporting millíons of cubic meters of crude oil end refined products, belonging to COCAWE (assaciation of companies of petroleum of Europe for health, environment and safety, that joint several petroleum companies). In Brazil they are about 18.000 Km of pipelines transporting millions of cubic meters of liquids and gases. In 1999, nine accidents were registered to COCAWE. Among those accidents one brought a fatal victim. The oil loss was of 171 m3, equivalent to O,2 parts per million of the total of the transported volume. Same considering the facts mentioned the costs involved in ao accident can be high. An accident of great proportions can bríng loss of human lives, severe environmental darnages, loss of drained product, loss . for dismissed profit and damages to the image of the company high recovery cost. In consonance with that and in some cases for legal demands, the companies are, more and more, investing in systems of Leak detection in pipelines based on computer algorithm that operate in real time, seeking wíth that to minimize still more the drained volumes. This decreases the impacts at the environment and the costs. In general way, all the systems based on softWare present some type of false alarm. In general a commitment exists betWeen the sensibílity of the system and the number of false alarms. This work has as objective make a review of thé existent methods and to concentrate in the analysis of a specific system, that is, the system based on hydraulic noise, Pressure Point Analyzis (PPA). We will show which are the most important aspects that must be considered in the implementation of a Leak Detection System (LDS), from the initial phase of the analysis of risks passing by the project bases, design, choice of the necessary field instrumentation to several LDS, implementation and tests. We Will make na analysis of events (noises) originating from the flow system that can be generator of false alarms and we will present a computer algorithm that restricts those noises automatically

Proposta de algoritmo para detecção de vazamentos em oleodutos utilizando análise freqüencial de sinais de pressão

Pipeline leak detection is a matter of great interest for companies who transport petroleum and its derivatives, in face of rising exigencies of environmental policies in industrialized and industrializing countries. However, existing technologies are not yet fully consolidated and many studies have been accomplished in order to achieve better levels of sensitivity and reliability for pipeline leak detection in a wide range of flowing conditions. In this sense, this study presents the results obtained from frequency spectrum analysis of pressure signals from pipelines in several flowing conditions like normal flowing, leakages, pump switching, etc. The results show that is possible to distinguish between the frequency spectra of those different flowing conditions, allowing recognition and announce of liquid pipeline leakages from pressure monitoring. Based upon these results, a pipeline leak detection algorithm employing frequency analysis of pressure signals is proposed, along with a methodology for its tuning and calibration. The proposed algorithm and its tuning methodology are evaluated with data obtained from real leakages accomplished in pipelines transferring crude oil and water, in order to evaluate its sensitivity, reliability and applicability to different flowing conditions

Sistema inteligente para detecção de vazamentos em dutos de petróleo usando transformada Wavelet e redes neurais

This work consists in the use of techniques of signals processing and artificial neural networks to identify leaks in pipes with multiphase flow. In the traditional methods of leak detection exists a great difficulty to mount a profile, that is adjusted to the found in real conditions of the oil transport. These difficult conditions go since the unevenly soil that cause columns or vacuum throughout pipelines until the presence of multiphases like water, gas and oil; plus other components as sand, which use to produce discontinuous flow off and diverse variations. To attenuate these difficulties, the transform wavelet was used to map the signal pressure in different resolution plan allowing the extraction of descriptors that identify leaks patterns and with then to provide training for the neural network to learning of how to classify this pattern and report whenever this characterize leaks. During the tests were used transient and regime signals and pipelines with punctures with size variations from ½' to 1' of diameter to simulate leaks and between Upanema and Estreito B, of the UN-RNCE of the Petrobras, where it was possible to detect leaks. The results show that the proposed descriptors considered, based in statistical methods applied in domain transform, are sufficient to identify leaks patterns and make it possible to train the neural classifier to indicate the occurrence of pipeline leaks

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

Sistemas de automação e manutenção de edifícios: concepção dos sistemas de detecção e protecção contra incêndios de uma unidade industrial

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Processamento embarcado aplicado a um sistema de deteccão de vazamentos

Embedded systems are widely spread nowadays. An example is the Digital Signal Processor (DSP), which is a high processing power device. This work s contribution consist of exposing DSP implementation of the system logic for detecting leaks in real time. Among the various methods of leak detection available today this work uses a technique based on the pipe pressure analysis and usesWavelet Transform and Neural Networks. In this context, the DSP, in addition to do the pressure signal digital processing, also communicates to a Global Positioning System (GPS), which helps in situating the leak, and to a SCADA, sharing information. To ensure robustness and reliability in communication between DSP and SCADA the Modbus protocol is used. As it is a real time application, special attention is given to the response time of each of the tasks performed by the DSP. Tests and leak simulations were performed using the structure of Laboratory of Evaluation of Measurement in Oil (LAMP), at Federal University of Rio Grande do Norte (UFRN)

Sistema de controle de escoamento de gás natural em dutos de distribuição com detecção de vazamentos utilizando redes neurais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Modelagem de sistemas de detecção de descargas atmosféricas na Amazônia

As descargas atmosféricas representam um dos maiores fatores de riscos para o setor elétrico, especialmente na Amazônia, uma região do mundo identificada com altas densidades de ocorrências e picos de corrente de raios. Nesse contexto, a rede STARNET (Sferics Timing And Ranging NETwork), único sistema de detecção de descargas elétricas atmosféricas, terrestre, gratuito, e contínuo, cobrindo toda a região Amazônica, foi escolhido para a geração de padrões de descargas atmosféricas necessários a otimização dos sistemas de proteção das linhas de transmissão por meio de sistema de monitoramento de descargas atmosféricas. Contudo, o funcionamento intermitente, observado nos diagramas operacionais das várias estações da rede STARNET, afeta o desempenho global do sistema, em especial a eficiência de detecção. Por isso, foi desenvolvido um modelo de uniformização dos dados de descargas atmosféricas em função da configuração da rede (número e localização dos sensores em operação), no objetivo final de editar mapas de índice ceráunico e densidades de raios confiáveis. Existem regiões da Amazônia que sempre apresentam anomalias positivas de densidade de raios como as regiões de Belém e Manaus, bem como o estado do Tocantins que afeitam as linhas de transmissão. Depois, a incidência de raios nas linhas de transmissão na Amazônia foi estimada a partir da distribuição de pico de correntes registrada pela RDR-SIPAM e da densidade de raios corrigida da rede STARNET. A avaliação do desempenho da rede STARNET tendo como referencia à rede de detecção de raios do Sistema de Proteção da Amazônia (RDR-SIPAM) mostrou também uma forte dependência da eficiência de detecção da rede STARNET em função do pico de corrente das descargas atmosféricas.

Estudo sobre desruptores endócrinos em sistemas aquáticos: detecção e perspectivas de tratamento das águas do Rio Aporé-MS/GO, utilizando-se adsorventes sólidos

Pós-graduação em Ciência dos Materiais - FEIS

Classificação de anomalias e redução de falsos positivos em sistemas de detecção de intrusão baseados em rede utilizando métodos de agrupamento

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Sistema de detecção e isolamento de falhas em sistemas dinâmicos baseado em identificação paramétrica

The present research aims at contributing to the area of detection and diagnosis of failure through the proposal of a new system architecture of detection and isolation of failures (FDI, Fault Detection and Isolation). The proposed architecture presents innovations related to the way the physical values monitored are linked to the FDI system and, as a consequence, the way the failures are detected, isolated and classified. A search for mathematical tools able to satisfy the objectives of the proposed architecture has pointed at the use of the Kalman Filter and its derivatives EKF (Extended Kalman Filter) and UKF (Unscented Kalman Filter). The use of the first one is efficient when the monitored process presents a linear relation among its physical values to be monitored and its out-put. The other two are proficient in case this dynamics is no-linear. After that, a short comparative of features and abilities in the context of failure detection concludes that the UFK system is a better alternative than the EKF one to compose the architecture of the FDI system proposed in case of processes of no-linear dynamics. The results shown in the end of the research refer to the linear and no-linear industrial processes. The efficiency of the proposed architecture may be observed since it has been applied to simulated and real processes. To conclude, the contributions of this thesis are found in the end of the text

Sistema híbrido para detecção e diagnóstico de falhas em sistemas dinâmicos

The industries are getting more and more rigorous, when security is in question, no matter is to avoid financial damages due to accidents and low productivity, or when it s related to the environment protection. It was thinking about great world accidents around the world involving aircrafts and industrial process (nuclear, petrochemical and so on) that we decided to invest in systems that could detect fault and diagnosis (FDD) them. The FDD systems can avoid eventual fault helping man on the maintenance and exchange of defective equipments. Nowadays, the issues that involve detection, isolation, diagnose and the controlling of tolerance fault are gathering strength in the academic and industrial environment. It is based on this fact, in this work, we discuss the importance of techniques that can assist in the development of systems for Fault Detection and Diagnosis (FDD) and propose a hybrid method for FDD in dynamic systems. We present a brief history to contextualize the techniques used in working environments. The detection of fault in the proposed system is based on state observers in conjunction with other statistical techniques. The principal idea is to use the observer himself, in addition to serving as an analytical redundancy, in allowing the creation of a residue. This residue is used in FDD. A signature database assists in the identification of system faults, which based on the signatures derived from trend analysis of the residue signal and its difference, performs the classification of the faults based purely on a decision tree. This FDD system is tested and validated in two plants: a simulated plant with coupled tanks and didactic plant with industrial instrumentation. All collected results of those tests will be discussed

Detecção de faltas em sistemas de distribuição de energia elétrica usando dispositivos programáveis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)