CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / O monitoramento e o diagnÃstico de falhas incipientes em transformadores de potÃncia imersos em Ãleo estÃo diretamente relacionados à avaliaÃÃo das condiÃÃes do sistema de isolamento. Neste estudo, estabelece-se o conceito de monitoramento e diagnÃstico, e em seguida tÃcnicas de monitoramento on-line sÃo discutidas. Um sistema de prÃ-diagnÃstico à elaborado baseado na utilizaÃÃo de um dispositivo on-line de monitoramento, Hydran da GE, para classificar a gravidade da situaÃÃo de falha detectada. Uma vez detectada uma situaÃÃo de falha, mÃdulos inteligentes de diagnÃstico de falhas incipientes, via redes neurais, podem ser utilizados para identificaÃÃo da falha interna do equipamento. Para completar a verificaÃÃo da qualidade dielÃtrica do lÃquido isolante, tambÃm à descrito um algoritmo inteligente, baseado em redes neurais, para diagnÃstico do estado do Ãleo atravÃs das grandezas fÃsico-quÃmicas. A relaÃÃo entre os atributos fÃsico-quÃmicos e as grandezas cromatogrÃficas referente ao Ãleo mineral tambÃm foram averiguadas. Foi desenvolvida, entÃo, a estimaÃÃo dos gases dissolvidos atravÃs das caracterÃsticas fÃsico-quÃmicas. Os mÃdulos de monitoramento on-line, diagnÃsticos do estado do Ãleo e de falhas incipientes, alÃm da estimaÃÃo dos gases dissolvidos, perfazem um sistema computacional de auxÃlio à operaÃÃo e manutenÃÃo. O sistema implementado apresenta resultados satisfatÃrios na implantaÃÃo em uma planta de usina termelÃtrica. / The monitoring and diagnosis of incipient fault in power transformers immerses in oil are directly related to the assessment of the isolation system conditions. In this research, it is established the concept of monitoring and diagnosis, after that, on-line monitoring techniques are discussed. A pre-diagnosis system is elaborated based on use of a monitoring on-line device, Hydran GE, to classify the situation gravity of the detected fault. Once detected a fault situation, intelligent modules of incipient fault diagnosis, by neural networks, can be used to identification of internal fault of the equipment. To complete the checking of the dielectric quality of the isolate liquid, it is also described an intelligent algorithm, based on neural networks, to diagnosis of the oil estate through physical-chemical attribute. The relation between physical-chemical attributes and chromatographic ones regarding to mineral oil were also verified. It was developed, then, the dissolved gases esteem through physicalchemical characteristics. The on-line monitoring modules, diagnosis of oil estate and incipient fault, besides dissolved gases esteem, constitute a computation aid system to operation and maintenance. The implemented system presents satisfied results in a thermoelectric power plant.

M. Ing. / Fault detection tools have gained popularity in recent years due to the increasing need for reliable and predictable equipments. Transformer bushings account for the majority of transformer faults. Hence, to uphold the integrity of the power transmission and dis- tribution system, a tool to detect and identify faults in their developing stage is necessary in transformer bushings. Among the numerous tools for bushings monitoring, dissolved gas analysis (DGA) is the most commonly used. The advances in DGA and data storage capabilities have resulted in large amount of data and ultimately, the data analysis crisis. Consequent to that, computational intelligence methods have advanced to deal with this data analysis problem and help in the decision-making process. Numerous computational intelligence approaches have been proposed for bushing fault detection. Most of these approaches focus on the accuracy of prediction and not much research has been allocated to investigate the interpretability of the decisions derived from these systems. This work proposes a rough set theory (RST) model for bushing fault detection based on DGA data analyzed using the IEEEc57.104 and the IEC 60599 standards. RST is a rule-based technique suitable for analyzing vague, uncertain and imprecise data. RST extracts rules from the data to model the system. These rules are used for prediction and interpreting the decision process. The lesser the number of rules, the easier it is to interpret the model. The performance of the RST is dependent on the discretization technique employed. An equal frequency bin (EFB), Boolean reasoning (BR) and entropy partition (EP) are used to develop an RST model. The model trained using EFB data performs better than the models trained using BR and EP. The accuracy achieved is 96.4%, 96.0% and 91.3% for EFB, BR and EP respectively. This work also pro poses an ant colony optimization (ACO) for discretization. A model created using ACO discretized achieved an accuracy of 96.1%, which is compatible with the three methods above. When considering the overall performance, the ACO is a better discretization tool since it produces an accurate model with the least number of rules. The rough set tool proposed in this work is benchmarked against a multi-layer perceptron (MLP) and radial basis function (RBF) neural networks. Results prove that RST modeling for bushing is equally as capable as the MLP and better than RBF. The RST, MLP and RBF are used in an ensemble of classifiers. The ensemble performs better than the standalone models.

This dissertation thesis is focused on the evaluation of the dissolved gas analysis in the power oil transformer diagnosis. This thesis derives from known, in standards, directives and literature shows realities which are fill in new pieces of knowledge as determining of gases important for evaluation of the transformer condition, specifying of current methods accuracy and investigating of accuracy change for interpretation of dissolved gases. The part of this thesis is the application of mathematic methods for detailed description of individual transformer failures and determining of dominant gas which are generating in power oil transformer. Obtain conclusion will be contribution for transformer diagnostics and will be applicable in industrial practice.

This dissertation is a systematic study of artificial intelligence (AI) applications for the diagnosis of power transformer incipient fault. The AI techniques include artificial neural networks (ANN, or briefly neural networks - NN), expert systems, fuzzy systems and multivariate regression. The fault diagnosis is based on dissolved gas-in-oil analysis (DGA). A literature review showed that the conventional fault diagnosis methods, i.e. the ratio methods (Rogers, Dornenburg and IEC) and the key gas method, have limitations such as the "no decision" problem. Various AI techniques may help solve the problems and present a better solution. Based on the IEC 599 standard and industrial experiences, a knowledge-based inference engine for fault detection was developed. Using historical transformer failure data from an industrial partner, a multi-layer perceptron (MLP) modular neural network was identified as the best choice among several neural network architectures. Subsequently, the concept of a hybrid diagnosis was proposed and implemented, resulting in a combined neural network and expert system tool (the ANNEPS system) for power transformer incipient diagnosis. The abnormal condition screening process, as well as the principle and algorithms of combining the outputs of knowledge based and neural network based diagnosis, were proposed and implemented in the ANNEPS. Methods of fuzzy logic based transformer oil/paper insulation condition assessment, and estimation of oil sampling interval and maintenance recommendations, were also proposed and implemented. Several methods of power transformer incipient fault location were investigated, and a 7Ã 21Ã 5 MLP network was identified as the best choice. Several methods for on-load tap changer (OLTC) coking diagnosis were also investigated, and a MLP based modular network was identified as the best choice. Logistic regression analysis was identified as a good auditor in neural network input pattern selection processes. The above results can help developing better power transformer maintenance strategies, and serve as the basis of on-line DGA transformer monitors. / Ph. D.

Os transformadores de potência são alguns dos elementos mais importantes dos sistemas elétricos. A confiabilidade e o bom funcionamento destes equipamentos são vitais para que as companhias de energia forneçam eletricidade com qualidade e segurança. Um dos principais parâmetros que envolvem a normalidade da operação dos transformadores é o estado da isolação interna formada pelo óleo mineral e o papel que cobre as bobinas. Danos nessa isolação resultam na degradação destes dielétricos e, por conseqüência, na diminuição da vida útil dos transformadores. Essa degradação, que advém de processos elétricos, térmicos, ou mesmo mecânicos, geram gases combustíveis cujas quantidades individuais podem indicar o tipo de falha e a gravidade do problema. Desta forma, é importante detectar os principais gases envolvidos. O objetivo deste trabalho é realizar análises e estudos quantitativos da presença de gases inflamáveis dissolvidos no óleo, surgidos através da degradação deste líquido isolante. O cerne deste trabalho está em elaborar ensaios de formação de arco no óleo e, posteriormente, aquecer o fluido para medir a quantidade dos gases combustíveis antes dissolvidos nele. Este estudo visa à melhoria na confiabilidade dos equipamentos projetados para detectar e monitorar o surgimento de gases inflamáveis no interior de transformadores de potência existentes em subestações de companhias de eletricidade. / Power transformers are some of the most important elements of electrical systems. The trustworthiness and the good functioning of this equipment permit power utilities to supply electricity with quality and security. One of the main parameters for transformer\'s operation normality is the state of the internal insulation formed by the mineral oil and the paper that covers the bobbins. Damages in this insulation cause its dielectric degradation and, consequently, the reduction of the equipment useful life. This degradation which originates from electrical, thermal, or even mechanical processes generates chemical products such as gases whose individual amounts may indicate the type of imperfection and gravity of the problem. That\'s why the detection of the main involved gases is important. This work intends to elaborate analyses and studies of the presence of inflammable gases dissolved in oil through the degradation of the insulating liquid. The principal topic of this work is the arc formation elaboration in the oil and later the heating of the oil to measure the amount of gases previously dissolved in it. This study also aims to improve the trustworthiness of the projected equipments in order to detect and monitor the sprouting of existing inflammable gases in the interior of power transformers in substations of power utilities.

Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro / A análise de gases dissolvidos tem sido aplicada há décadas como a principal técnica de manutenção preditiva para diagnosticar defeitos incipientes em transformadores de potência, tendo em vista que a decomposição do óleo mineral isolante produz gases que permanecem dissolvidos na fase líquida. Entretanto, apesar da importância desta técnica, os métodos de diagnóstico mais conhecidos são baseados em constatações de modelos termodinâmicos e composicionais simplificados para a decomposição térmica do óleo mineral isolante, em conjunto com dados empíricos. Os resultados de simulação obtidos a partir desses modelos não reproduzem satisfatoriamente os dados empíricos. Este trabalho propõe um modelo termodinâmico flexível aprimorado para mimetizar o efeito da cinética de formação de sólidos como restrição ao equilíbrio e seleciona, entre quatro modelos composicionais, aquele que apresenta o melhor desempenho na simulação da decomposição térmica do óleo mineral isolante. Os resultados de simulação obtidos a partir do modelo proposto apresentaram uma melhor adequação a dados empíricos do que aqueles obtidos a partir dos modelos clássicos. O modelo propostofoi, ainda, aplicado ao desenvolvimento de um método de diagnóstico com base fenomenológica.Os desempenhos desta nova proposta fenomenológica e de métodos clássicos de diagnóstico por análise de gases dissolvidos foram comparados e discutidos; o método proposto alcançou desempenho superior a vários métodos usualmente empregados nessa área do conhecimento. E, ainda, um procedimento geral para a aplicação do novo método de diagnóstico é descrito / The dissolved gas analysis has been applied for decades as the main predictive maintenance technique for diagnosing incipient faults in power transformers since the decomposition of the mineral insulating oil produces gases that remain dissolved in the liquid phase. Nevertheless, the most known diagnostic methods are based on findings of simplified thermodynamic and compositional models for the thermal decomposition of mineral insulating oil, in addition to empirical data. The simulations results obtained from these models do not satisfactorily reproduce the empirical data. This work proposes a flexible thermodynamic model enhanced to mimic the kinetic effect of solid formation as a restriction to equilibrium and selects, among four compositional models, the one offering the best performance on the simulation of the thermal decomposition of mineral insulating oil. The simulation results obtained from the proposed model showed better adequacy to reported data than the results obtained from the classical models. The proposed model was also applied in the development of a diagnostic method with a phenomenological basis. The performances of this new phenomenological proposition and of classical dissolved gas analysis diagnostic methods are compared and discussed; the proposed method achieved a performance superior to several methods usually employed in this area of knowledge.Also, a general procedure for the application of the new diagnostic method is described

CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / O diagnÃstico de falhas incipientes em transformadores de potÃncia imersos em Ãleo està diretamente relacionado à avaliaÃÃo das condiÃÃes do sistema de isolamento. Este estudo aborda a relaÃÃo entre os gases dissolvidos no Ãleo e a qualidade do Ãleo mineral isolante utilizado em transformadores de potÃncia. As redes neurais artificiais sÃo utilizadas na abordagem da avaliaÃÃo das condiÃÃes operacionais do Ãleo isolante em transformadores de potÃncia, que à caracterizada por um comportamento dinÃmico nÃo-linear. As condiÃÃes de operaÃÃo e a integridade do sistema de isolamento de um transformador de potÃncia podem ser inferidas atravÃs das anÃlises fÃsico-quÃmicas e cromatogrÃficas (AnÃlise de GÃs Dissolvido). Estes ensaios permitem estabelecer procedimentos de operaÃÃo e manutenÃÃo do equipamento e normalmente sÃo realizados simultaneamente. Esta tese de doutorado propÃe um mÃtodo que pode ser usado para extrair informaÃÃes cromatogrÃficas usando as anÃlises fÃsico-quÃmicas atravÃs de redes neurais artificiais. As anÃlises atuais das propriedades fÃsico-quÃmicas fornecem apenas diagnÃstico do estado do Ãleo, o que nÃo permite o diagnÃstico de falhas incipientes. Acredita-se que, as concessionÃrias de energia podem melhorar a confiabilidade na previsÃo de falhas incipientes a um custo menor com este mÃtodo, uma vez que apenas um ensaio à necessÃrio. Os resultados mostraram que esta estratÃgia à promissora com mÃdia de acertos em diagnÃsticos de falhas maiores que 72%. O objetivo deste trabalho à a aplicaÃÃo direta do diagnÃstico de falhas incipientes atravÃs da utilizaÃÃo de propriedades fÃsico-quÃmicas, sem a necessidade de fazer uma cromatografia do Ãleo. / The diagnosis of incipient fault in power transformers immerses in oil are directly related to the assessment of the isolation system conditions. This search is about the relationship between dissolved gases and the quality of the insulating mineral oil used in power transformers. Artificial Neural Networks are used to approach operational conditions assessment issue of the insulating oil in power transformers, which is characterized by a nonlinear dynamic behavior. The operation conditions and integrity of a power transformer can be inferred by analysis of physicochemical and chromatographic (DGA â Dissolved Gas Analysis) profiles of the isolating oil. This tests allow establishing procedures for operating and maintaining the equipment and usually are performed simultaneously. This work proposes a method that can be used to extract chromatographic information using physicochemical analysis through Artificial Neural Networks. The present analysis of physicochemical properties only provide a diagnostic tool for the oil quality, which does not allow the diagnosis of incipient faults. ItÂs believed that, the power utilities could improve reliability in the prediction of incipient failures at a lower cost with this method, since only one test is required. The results show this strategy might be promising with an average accuracy for diagnosis of faults greater than 72%. The purpose of this work is the direct implementation of the diagnosis of incipient faults through the use of physicochemical properties without the need to make an oil chromatography.

Submitted by JÚLIO HEBER SILVA (julioheber@yahoo.com.br) on 2017-07-21T17:52:36Z No. of bitstreams: 2 Dissertação - Tiago Henrique Vivas e Silva - 2017.pdf: 5148275 bytes, checksum: 451ab8d12dacefd5609d711aa1677179 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2017-07-24T11:16:07Z (GMT) No. of bitstreams: 2 Dissertação - Tiago Henrique Vivas e Silva - 2017.pdf: 5148275 bytes, checksum: 451ab8d12dacefd5609d711aa1677179 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2017-07-24T11:16:08Z (GMT). No. of bitstreams: 2 Dissertação - Tiago Henrique Vivas e Silva - 2017.pdf: 5148275 bytes, checksum: 451ab8d12dacefd5609d711aa1677179 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017-05-25 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / This work have its main theme on the maintenance in Power Transformers in energy substations. Power Transformers have great importance in power transmission and distribution systems. In addition to being essential to perform the transformation between diferent levels of electrical voltage from generation to consumption, the cost of these equipments represents a considerable part of the investment in the system. A failure in a transformer can compromise the supply of electricity to an entire region of the city, which represents a lack of billing and fines to the power distribution company, as well as the repair costs of the equipment that failed. In this dissertation one of the main techniques used to diagnose power transformers using the Dissolved Gas Analysis (DGA) are discussed, as well as the use of Fuzzy Logic in conjunction with the diferente analysis techniques. The differential of this work is the development of a computational tool that allows the grafical visualization of diagnosis evolution for each equipment over time and provides a final result by a flowchart that considers all diagnosis of the traditional techniques approached with application of Fuzzy Logic. The result obtained is the development of a software that implements the proposed methodology and graphically presents the diagnostics of each equipment present in the company’s database. The software allows the analysis of the current operational state of the equipment and his evolution over time, subsidizing the decision of the maintenance professional regarding maintenance in the equipment. / Este trabalho tem como tema central o planejamento da manutenção em transformadores de potência em subestações. Os transformadores de potência têm uma grande importância nos sistemas de transmissão e distribuição de energia elétrica. Além de serem essenciais para efetuar a transformação entre os diferentes níveis de tensão elétrica ao longo do sistema desde a geração até o consumo, o valor destes equipamentos representa uma parcela considerável do investimento das concessionárias no sistema. Uma falha em um transformador de potência pode comprometer o fornecimento de energia elétrica para uma região inteira da cidade, o que representa falta de faturamento e multas para a concessionária, além dos próprios custos de reparação do equipamento que falhou. Nesta dissertação é abordada uma das principais técnicas utilizadas para diagnósticos de transformadores de potência: a Análise de Gases Dissolvidos (AGD), bem como a utilização da lógica Fuzzy em conjunto com os diferentes métodos de análise desta técnica. O diferencial deste trabalho está no desenvolvimento de uma ferramenta computacional que permite a visualização gráfica da evolução do diagnóstico de cada equipamento ao longo do tempo e fornece um resultado final através de um fluxograma que considera os diagnósticos de todas as técnicas tradicionais abordadas com a aplicação da lógica Fuzzy. O resultado obtido é o desenvolvimento de um software que implementa a metodologia proposta e apresenta, de forma gráfica, os diagnósticos de cada equipamento presente no banco de dados da empresa. O software permite a análise do atual estado operacional do equipamento e a evolução deste diagnóstico ao longo do tempo, subsidiando a tomada de decisão do profissional da manutenção quanto às manutenções no equipamento.

Os transformadores de potência são alguns dos elementos mais importantes dos sistemas elétricos. A confiabilidade e o bom funcionamento destes equipamentos são vitais para que as companhias de energia forneçam eletricidade com qualidade e segurança. Um dos principais parâmetros que envolvem a normalidade da operação dos transformadores é o estado da isolação interna formada pelo óleo mineral e o papel que cobre as bobinas. Danos nessa isolação resultam na degradação destes dielétricos e, por conseqüência, na diminuição da vida útil dos transformadores. Essa degradação, que advém de processos elétricos, térmicos, ou mesmo mecânicos, geram gases combustíveis cujas quantidades individuais podem indicar o tipo de falha e a gravidade do problema. Desta forma, é importante detectar os principais gases envolvidos. O objetivo deste trabalho é realizar análises e estudos quantitativos da presença de gases inflamáveis dissolvidos no óleo, surgidos através da degradação deste líquido isolante. O cerne deste trabalho está em elaborar ensaios de formação de arco no óleo e, posteriormente, aquecer o fluido para medir a quantidade dos gases combustíveis antes dissolvidos nele. Este estudo visa à melhoria na confiabilidade dos equipamentos projetados para detectar e monitorar o surgimento de gases inflamáveis no interior de transformadores de potência existentes em subestações de companhias de eletricidade. / Power transformers are some of the most important elements of electrical systems. The trustworthiness and the good functioning of this equipment permit power utilities to supply electricity with quality and security. One of the main parameters for transformer\'s operation normality is the state of the internal insulation formed by the mineral oil and the paper that covers the bobbins. Damages in this insulation cause its dielectric degradation and, consequently, the reduction of the equipment useful life. This degradation which originates from electrical, thermal, or even mechanical processes generates chemical products such as gases whose individual amounts may indicate the type of imperfection and gravity of the problem. That\'s why the detection of the main involved gases is important. This work intends to elaborate analyses and studies of the presence of inflammable gases dissolved in oil through the degradation of the insulating liquid. The principal topic of this work is the arc formation elaboration in the oil and later the heating of the oil to measure the amount of gases previously dissolved in it. This study also aims to improve the trustworthiness of the projected equipments in order to detect and monitor the sprouting of existing inflammable gases in the interior of power transformers in substations of power utilities.

Οι μετασχηματιστές ισχύος αποτελούν τα κρισιμότερα στοιχεία ενός Συστήματος Ηλεκτρικής Ενέργειας από την άποψη κόστους, χρησιμότητας και επικινδυνότητας. Επομένως είναι ιδιαίτερα σημαντικός ο έλεγχος της υγείας των μετασχηματιστών και της λειτουργικής τους ικανότητας. Η παρούσα διπλωματική εργασία ασχολείται με το διαγνωστικό έλεγχο των μεγάλων μετασχηματιστών ελαίου. Για το σκοπό αυτό θεωρείται αναγκαίο να γίνει πρώτα μία αναλυτική αναφορά στους μετασχηματιστές και στις ιδιότητές τους. Στο κεφάλαιο 1 γίνεται μία σύντομη εισαγωγή σχετική με τα Σ.Η.Ε. ώστε να καταστεί σαφής ο ρόλος των μετασχηματιστών σε αυτά. Στο κεφάλαιο 2 περιγράφονται λεπτομερώς οι αρχές λειτουργίας και τα κατασκευαστικά στοιχεία των μετασχηματιστών καθώς και τα προβλήματα που προκύπτουν σε αυτούς εξαιτίας της λειτουργίας τους ή από την πάροδο των ετών. Το κεφάλαιο 3 ασχολείται με τη λειτουργική κατάσταση και τη διάρκεια ζωής των μετασχηματιστών και την εξάρτησή τους από την κατάσταση της μόνωσης. Στο κεφάλαιο 4 παρατίθενται όλες οι κλασικές μέθοδοι που χρησιμοποιούνται για την παρακολούθηση και τη διάγνωση σφαλμάτων στους μετασχηματιστές. Επίσης περιγράφονται η κατάταξη των μετασχηματιστών ανάλογα με την ικανότητά τους να παραμείνουν σε λειτουργία και η ένταξη της παρακολούθησής τους στον έλεγχο του συστήματος. Το κεφάλαιο 5 επικεντρώνεται στη μέθοδο Duval, μία μέθοδο διάγνωσης που συγκαταλέγεται στην κατηγορία των Χημικών Μεθόδων και ειδικότερα της Ανάλυσης των Διαλυμένων Αερίων στο λάδι. Στο κεφάλαιο αυτό γίνεται η περιγραφή της μεθόδου και η παράθεση του προγράμματος που εφαρμόζει τη μέθοδο. Τα παραρτήματα αποσαφηνίζουν κάποιες λεπτομέρειες σχετικές με τη μέθοδο Duval, χρήσιμες για την κατάστρωση του κώδικα. / Power transformers are the most critical components of an Electric Power System (E.P.S.) as far as their cost, usefulness and level of risk are concerned. Therefore their maintenance as well as their health and ability to stay in service check are of great importance. This thesis deals with the diagnostics of large oil immersed transformers. Consequently it is considered necessary to begin with a detailed description of power transformers and their attributes. In Chapter 1 a short introduction of E.P.S. is taking place in order to clarify the role of power transformers in them. In Chapter 2 the principles of operation, the manufacturing elements as well as the malfunctions that occur in a transformer because of their use or in the course of time are described in detail . Chapter 3 deals with the operation condition, life-span and the dependency of a transformer on the insulation system condition. In Chapter 4 all the common used techniques for condition monitoring and fault diagnosis of a transformer are displayed. Furthermore the order of the transformers depending on their ability to maintain in operative condition is described as well as the incorporation of their monitoring in the system inspection. Chapter 5 is focused on the Duval method which is a chemical method for fault diagnosis and more specifically a dissolved gas analysis. In this chapter the Duval method is described in detail along with the description of the program that uses this method. The adjuncts clarify some details regarding the Duval method which are necessary for the comprehension of the program.