Orientador: Paulo Sollero / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica / Made available in DSpace on 2018-08-18T19:31:17Z (GMT). No. of bitstreams: 1 QuispeRodriguez_Rene_M.pdf: 18563106 bytes, checksum: 3b10d1a137086184fd58033d26af0222 (MD5) Previous issue date: 2011 / Resumo: A aplicação de adesivos para união de materiais cresceu consideravelmente no decorrer dos últimos anos, sendo que tal crescimento se deve aos benefícios proporcionados pelos adesivos, quando comparados aos métodos tradicionais de união, como solda ou utilização de parafusos. Na indústria, características como fácil aplicabilidade, melhor distribuição de tensões, prolongada vida útil, maior absorção de impactos e vibrações, menores custos de produtos e processos, tornam a utilização de adesivos soluções interessantes e competitivas. Existe então uma necessidade especifica de análise e da criação de ferramentas que ajudem no projeto de juntas coladas. O presente trabalho visa suprir em certa forma essa necessidade, mediante o estudo e implementação de modelos analíticos e critérios de falha. Para a validação numérica foi utilizado o método dos elementos finitos (MEF), mediante o uso do software comercial ABAQUS. Os modelos analíticos, numéricos e critérios de falha foram introduzidos em um software de fácil uso, denominado "KISPEO". Este software foi programado em sua maior parte mediante o aplicativo GUI (Graphical User Interface) do MATLAB. O software, que conta com interfaces amigáveis, é focado na análise das distribuições de tensões em juntas coladas de sobreposição simples (SLJ). Os modelos implementados no presente trabalho foram logo validados com ensaios experimentais normalizados segundo a norma ASTM (American Society for Testing and Materials) / Abstract: Application of adhesives in bonded joints has increased considerably over recent years. This growth is due to the benefits provided by adhesives, when compared to conventional joining methods, like rivets, bolts or welding. In the industry, characteristics as easy applicability, better stress distributions, improved service life, better impact and vibration absorption, less process and product costs, make adhesives an interesting and competitive option. Therefore, there is a specific need for analysis and design tools that can provide physical insight and accurate results for bonded joint applications. The present work aims to fulfill partially this need, studying and implementing several analytical models and failure criteria for bonded joints. For the numerical validation was utilized the Finite Element Method (FEM), using the commercial software ABAQUS. Analytical methods, numerical models and failure criteria were introduced in a user-friendly software, named "KISPEO". This software was implemented using the applicative GUI (Graphical User Interface) of MATLAB. The software, which features graphical interfaces, is focused in stress distribution and failure criteria analysis of Single Lap Joints (SLJ). Finally, implemented models were validated with experimental tests according to the ASTM (American Society for Testing and Materials) standard / Mestrado / Mecanica dos Sólidos e Projeto Mecanico / Mestre em Engenharia Mecânica

Fault location within electric power systems is an important topic that helps reduce outage duration and increases reliability of the system. This paper explores the topic of fault location using traveling waves generated by fault conditions and the discrete wavelet transform used for time-frequency analysis. The single-ended and double-ended traveling wave methods are presented and evaluated on a single circuit and double circuit 500kV system modeled using MATLAB SIMULINK. Results are compared on the basis of wavelet used for analysis, sampling rate, and fault resistance.

Uninterrupted power supply is an important requirement for electric ship since it has to confront frequent travel and hostilities. However, the occurrence of faults in the shipboard power systems interrupts the power service continuity and leads to the severe damage on the electrical equipments. Faults need to be quickly detected and isolated in order to restore the power supply and prevent the massive cascading outage effect on the electrical equipments. This thesis presents an Artificial Neural Network (ANN) based method for the fault classification and location in MVDC shipboard power systems using the transient information in the fault voltage and current waveforms. The proposed approach is applied to the cable of an equivalent MVDC system which is simulated using PSCAD. The proposed method is efficient in detecting the type and location of DC cable faults and is not influenced by changes in electrical parameters like fault resistance and load.

No description available.

In this dissertation, we propose two fault simulators, called HOPE and HOPE2, and an autolllatic test pattern generator (ATPG), called ATHENA, for synchronous and asynchronous sequential circuits. HOPE is a parallel fault simulator for synchronous sequential circuits. In HOPE, a packet of 32 faults is simulated in parallel. Several new heuristics are employed in HOPE to accelerate the parallel fault simulation. The heuristics are 1) a reduction of faults to be simulated in parallel, 2) a new fault injection method called functional fault injection, and J) a combination of static and dynamic fault ordering methods. According to our experiments, HOPE is about 2.2 times, on the average, faster than a competing fault simulator, called PROOFS (1]--[2]. for 16 ISCAS89 benchmark circuits [3]. HOPE2 and ATHENA are a fault simulator and an A TPG for asynchronous sequential circuits, respectively. The key idea employed in HOPE2 and ATHENA is 10 transform an asynchronous sequential circuit into a synchronous sequential circuit through remodeling memory elements. We proposed various modeling techniques which transform any asynchronous sequential circuit into a synChronous sequential circuit. Once an asyncllfonous circuit is transformed into a synchronous circuit, various techniques developed for synchronous sequential circuits are employed in HOPE2 and ATHENA. HOPE2 employs the parallel simulation techniques of HOPE. ATHENA employs the back algorithm [4] for test generation, and the parallel fault simulation teChnique for fault simulation. HOPE2 and ATHENA can manage industrial circuits consisting of latches, flip-flops with set/reset, tristate gates, BUS elements, bi-directional I/O pins, mutiplexers, ROMs and RAMs. OUf experimental results on various industrial circuits show that HOPE2 is about two times faster than a commercial fault simulator, the Verifault fault simulator of Cadence, while requiring much smaller memory size. ATHENA also shows high performance for various industrial circuits. / Ph. D.

Modernized and advanced electricity transmission and distribution infrastructure ensures reliable, efficient, and affordable delivery of electric power. The complexity of fault location problem increases with the proliferation of unusual topologies and with the advent of renewable energy-based power generation in the smart grid environment. The proliferation of new Intelligent Electronic Devices (IEDs) provides a venue for the implementation of more accurate and intelligent fault location methods. This dissertation focuses on intelligent fault location methods for smart power grids and it aims at improving fault location accuracies and decreasing the cost and the mean time to repair damaged equipment in major power outages subsequently increasing the reliability of the grid. The developed methods utilize wavelet transformation to extract the traveling wave information in the very fast voltage and current transients which are initiated immediately after a fault occurs, support vector machines to classify the fault type and identify the faulted branches and finally Bewley diagrams to precisely locate the fault. The approach utilizes discrete wavelet transformation (DWT) for analysis of transient voltage and current measurements. The transient wavelet energies are calculated and utilized as the input for support vector machine (SVM) classifiers. SVM learns the mapping between inputs (i.e. transient voltages and/or currents wavelet energies) and desired outputs (i.e. faulty phase and/or faulty section) through processing a set of training cases. This dissertation presents the proposed methodologies applied to three complex power transmission systems. The first transmission system is a three-terminal (teed) three-phase AC transmission network, a common topology in high- and extra high-voltage networks. It is used to connect three substations that are wide apart from each other through long transmission lines with a tee-point, which is not supported by a substation nor equipped with a measuring device. The developed method overcomes the difficulties introduced by the discontinuity: the tee point. The second topology is a hybrid high voltage alternative current (HVAC) transmission line composed of an overhead line combined with an underground cable. The proposed fault location method is utilized to overcome the difficulties introduced by the discontinuity at the transition point from the overhead line to the underground cable and the different traveling wave velocities along the line and the cable. The third topology is a segmented high voltage direct current (HVDC) transmission line including an overhead line combined with an underground cable. This topology is widely utilized to transmit renewable energy-based electrical power from remote locations to the load centers such as from off-shore wind farms to on-shore grids. This dissertation introduces several enhancements to the existing fault type and fault location algorithms: improvement in the concept of fault type classification and faulty section identification by using SVMs with smaller inputs and improvements in the fault location in the complex configurations by utilizing less measurements from the terminals. / Ph. D.

Fault location detection plays a crucial role in power transmission network, especially on security, stabilization and economic aspects. Accurate fault location detection in transmission network helps to speed up the restoration time, therefore, reduce the outage time and improve the system reliability [1]. With the development of Wide Area Measurement System (WAMS) and Phasor Measurement Unit (PMU), various fault location algorithms have been proposed. The purpose of this work is to determine, modify and test the most appropriate fault location method which can be implemented with a PMU only linear state estimator. The thesis reviews several proposed fault location methods, such as, one-terminal [2], multi-terminal [3]-[11] and travelling wavelets methods [12]-[13]. A Two-stage fault location algorithm using PMU voltage measurements proposed by Q. Jiang [14] is identified as the best option for adaption to operate with a linear state estimator. The algorithm is discussed in details and several case studies are made to evaluate its effectiveness. The algorithm is shown to be easy to implement and adapt for operation with a linear state estimator. It only requires a limited number of PMU measurements, which makes it more practical than other existing methods. The algorithm is adapted and successfully tested on a real linear state estimator monitored high voltage transmission network. / Master of Science

The rapid growth of the electric power system has in recent decades resulted in an increase of the number of transmission lines and total power outage in Norway. The challenge of a fast growing electrical grid has also resulted in huge increases of overhead lines and their total length. These lines are experiencing faults due to various reasons that cause major disruptions and operating costs of the transmission system operator (TSO). Thus, it’s important that the location of faults is either known or can be estimated with reasonably high accuracy. This allows the grid owner to save money and time for inspection and repair, as well as to provide a better service due to the possibility of faster restoration of power supply and avoiding blackouts.  Fault detection and classification on transmission lines are important tasks in order to protect the electrical power system. In recent years, the power system has become more complicated under competitive and deregulated environments and a fast fault location technique is needed to maintain security and supply in the grid. This thesis compares and evaluates different methods for classification of fault type and calculation of conventional one-side and two-side based fault location algorithms for distance to fault estimation.  Different algorithm has been implemented, tested and verified to create a greater understanding of determinants facts that affect distance to faults algorithm’s accuracy.  Implemented algorithm has been tested on the data generated from a number of simulations in Simulink for a verification process in implemented algorithms accuracy. Two types of fault cases have also been simulated and compared for known distance to fault estimation.

Electric power systems are among the most complex man made systems on the world. Most of the time, they operate under quasi-steady state. With the ever increasing load demand and the advent of the deregulated power market recently, the power systems are pushed more often to operate close to their design limits and with more uncertainty of the system operating mode. With the increasing complexity and more interconnected systems, power systems are operating closer to their performance limits. As a result, maintaining system security and facilitating efficient system operation have been challenging tasks. Transmission systems are considered the most vital components in power systems connecting both generating/substation and consumer areas with several interconnected networks. In the past, they were owned by regulated, vertically integrated utility companies. They have been designed and operated so that conditions in close proximity to security boundaries are not frequently encountered. However, in the new open access environment, operating conditions tend to be much closer to security boundaries, as transmission use is increasing in sudden and unpredictable directions. Transmission unbundling, coupled with other regulatory requirements, has made new transmission facility construction more difficult. Unfortunately these transmission lines are frequently subjected to a wide variety of faults. Thus, providing proper protective functions for them is essential. Generally the protection of Extra High Voltage (EHV) and Ultra High Voltage (UHV) transmission lines are carried out by the use of distance relays in view of the fact that they provide fast fault clearance and system coordination. Transmission line relaying involves detection, classification and location of transmission line faults. Fast detections of faults enable quick isolation of the faulty line from service and hence, protecting it from the harmful effects of fault. Classification of faults means identification of the type of fault and faulted line section, and this information is required for finding the fault location and assessing the extent of repair work to be carried out. Accurate fault location is necessary for facilitating quick repair and restoration of the line, to improve the reliability and availability of the power supply. Generally, the protection system using conventional distance relaying algorithm involves three zones. The first zone (Z1) of the relay is set to detect faults on 80%90% of the protected line without any intentional time delay. The second zone (Z2) is set to protect the remainder of the line plus an adequate margin. Second zone relays are time delayed for 1530 cycles to coordinate with relays at remote bus. The settings of the third zone (Z3) ideally will cover the protected line, plus all of the longest line leaving the remote station. Z3 of a distance relay is used to provide the remote backup protection in case of the failure of the primary protection. Since Z3 covers an adjacent line, a large infeed (outfeed) from the remote terminal causes the relay to underreach (overreach). Thus, a very large load at the remote terminal may cause distance relays to mal-operate. Settings for conventional distance relays are selected to avoid overreach/underreach operation under the worst case scenarios. Studies of significant power system disturbances reported by North American Electric Reliability Council (NERC) indicate that protective relays are involved, one way or another, in 75% of the major disturbances and the most troublesome ones are backup protection relays. With their limited view of the interconnected network based on their locally measured inputs, conventional backup protection relays generally take actions to protect a localized region of the network without considering the impact on the whole network. Relay mal-operations or unintended operations due to overload, power swing, and relay hidden failure are the main factors contributing to the blackouts. Most of the problems are associated with relays tripping too many healthy lines. Since a relay makes the decision automatically to remove a component from the system according to its internal mechanism, the relay mal-operation or unintended operation can make an effective influence on the system stability. Approaches to reduce the relay misbehavior need to be identified. Real time monitoring tools to assess the relay misbehavior are needed, providing the system operator, the accurate information about unfolding events. Existing transmission line protection scheme still has drawbacks. Advanced fault analysis mechanism to enhance the system dependability and security simultaneously is desirable. Relay settings play a significant role in major blackouts. So correct settings should be calculated and coordinated by suitable studies. Attempts are to be made to employ highly accurate AI techniques in protective system implementation. The research work focussed on developing knowledge based intelligent tools for the improving the transmission system security. A process to obtain knowledgebase using SVMs for ready post-fault diagnosis purpose is developed. SVMs are used as Intelligent tool for identifying the faulted line that is emanating from a substation and finding the distance from the substation. The approach uses phasor values of the line voltages and currents after the fault has been detected. The approach is particularly important for post-fault diagnosis of any mal-operation of relays following a disturbance in the neighboring line connected to the same substation. This may help in improving the fault monitoring/diagnosis process and coordination of the protective relays, thus assuring secure operation of the power systems. The approach based on SVMs, exploits the first part of this goal. For comparison, a classifier and regression tools based on the RBFNNs was also investigated. The RBFNNs and SVM networks are introduced and considered as an appropriate tool for pattern recognition problems. Results on a practical 24Bus equivalent EHV transmission system of Indian Southern region and on IEEE39 bus New England system are presented to illustrate the proposed method. In a large connected power network, the number of generators are more in number and their set patterns number will be large. As the line flows are sensitive to generator set patterns, it is difficult to consider all the combinations of generators while simulating the training and testing patterns as input to SVMs. To simulate the training and testing patterns corresponding to possible changes in line flows to meet the load in the present deregulated environment, line flow sensitive generators set to be identified/merit-listed. In this regard, to identify the most sensitive generators for a particular line of interest, a method from the literature is adopted and developed a software program based on the graph theory concepts. Case studies on generator contributions towards loads and transmission lines are illustrated on an equivalent 33bus system, a part of Indian Northern grid with major part of Uttar Pradesh and also with an equivalent 246bus system of practical Indian Southern grid. A distance relay coordination approach is proposed using detailed simulation studies, taking into account various operating conditions and fault resistances. Support Vector Machines as a pattern classifier is used for obtaining distance relay coordination. The scheme uses the apparent impedance values observed during fault as inputs. SVMs are used to build the underlying concept between reach of different zones and the impedance trajectory during fault. An improved performance with the use of SVMs, keeping the reach when faced with different fault conditions as well as line flow changes are illustrated with an equivalent 246bus system of practical Indian Southern grid and also with an equivalent 265bus system of practical Indian Western grid. A strategy of Supportive System is described to aid the conventional protection philosophy in combating situations where protection systems are mal-operated and/or information is missing and provide selective and secure coordination. Highly accurate identification/discrimination of zones plays a key role in effective implementation of the region-wide supportive system. This typically requires a multiclass SVM classifier to effectively analyze/build the underlying concept between reach of different zones and the apparent impedance trajectory during fault. Different multiclass methods are compared for their performance with respect to accuracy, number of iterations, number of support vectors, training and testing time. The performance analysis of these methods is presented on three data sets belonging to the training and testing patterns of three supportive systems for a region, part of a network, which is an equivalent 265bus system of practical Indian Western grid.

Com o aumento de uso de fontes renováveis para geração de energia e o aprimoramento da tecnologia de conversores fonte de tensão (VSC – Voltage Source Converter), sistemas baseados em corrente contínua não só se tornaram viáveis como também se tornaram uma alternativa vantajosa em diversas situações. O uso de diversos conversores conectados em uma rede, isto é uma rede VSC-HVDC multiterminal, se apresenta como um caminho para a conexão de diversas fontes, como geradores eólicos e solares de maneira eficiente e economicamente vantajosa. No entanto, este tipo de rede possui algumas limitações, por exemplo, é mais sensível a faltas que um sistema de corrente contínua baseado em conversores do tipofonte de corrente (CSC – Current Source Converter). Desta forma, o estudo de faltas em sistemas VSC-HVDC é necessário para o desenvolvimento de mecanismos de proteção para estes sistemas. Neste contexto é importante o desenvolvimento de metodologias para a localização de faltas em sistemas MTDC, uma vez que este tipo de informação pode ajudar as equipes de manutenção a encontrarem as falhas e resolverem o problema da maneira mais rápida possível. Embora existam diversos estudos e metodologias desenvolvidas para sistemas de corrente alternada, ou para sistemas de corrente contínua de dois terminais, os estudos em redes de corrente contínua multiterminais ainda são poucos e em geral atendem a apenas um tipo de rede, mostrando assim a necessidade de mais estudos na área. Desta forma, o objetivo desta dissertação de mestrado é o desenvolvimento de uma metodologia localização de faltas em um sistema HVDC multiterminal, que contará também com técnicas já propostas na literatura para a detecção das falhas.Neste documento são mostrados o embasamento teórico, os estudos realizados para o desenvolvimento do tema, bem como os resultados obtidos para a localização de faltas em um sistema teste de simulação. / The increase of the use of renewable sources for power generation and the enhancement of Voltage Source Converter (VSC) technology, DC-based systems have become viable and an advantageous alternative in many situations. The use of several converters connected in a network, ie a multi-terminal VSC-HVDC network, is presented as a way to connect several sources, such as wind and solar generators in an efficient and economically advantageous way. However, this type of network has some limitations, for example, it is more sensitive to faults than a DC current system based on Current Source Converter (CSC). Therefore, the study of faults in VSC-HVDC systems is necessary for the development of protections for these systems. In this context it is important to develop fault location methodologies in MTDC systems since this type of information can help maintenance teams to find fault and solve the problem as quickly as possible. Although there are several studies and methodologies developed for alternating current systems or for two-terminal DC systems, there are few studies on multiterminal DC networks and this studies generally address only one type of network, thus showing the need for more studies in the area. Thus, the objective of this master\'s thesis is the development of a fault localization methodology in a multi-terminal HVDC system, which will also have techniques already proposed in the literature for the detection of faults. In this document are shown the theoretical background, the studies carried out for the development of the theme, as well as the results obtained for fault localization in a simulation test system.