Implementação em FPGA de compensadores de desvios para conversor analógico digital intercalado

This work presents the modeling and FPGA implementation of digital TIADC mismatches compensation systems. The development of the whole work follows a top-down methodology. Following this methodology was developed a two channel TIADC behavior modeling and their respective offset, gain and clock skew mismatches on Simulink. In addition was developed digital mismatch compensation system behavior modeling. For clock skew mismatch compensation fractional delay filters were used, more specifically, the efficient Farrow struct. The definition of wich filter design methodology would be used, and wich Farrow structure, required the study of various design methods presented in literature. The digital compensation systems models were converted to VHDL, for FPGA implementation and validation. These system validation was carried out using the test methodology FPGA In Loop . The results obtained with TIADC mismatch compensators show the high performance gain provided by these structures. Beyond this result, these work illustrates the potential of design, implementation and FPGA test methodologies.

Diagnóstico automático de eventos e distúrbios em unidades geradoras e usinas utilizando lógica fuzzy

The electric power systems are getting more complex and covering larger areas day by day. This fact has been contribuiting to the development of monitoring techniques that aim to help the analysis, control and planning of power systems. Supervisory Control and Data Acquisition (SCADA) systems, Wide Area Measurement Systems and disturbance record systems. Unlike SCADA and WAMS, disturbance record systems are mainly used for offilne analysis in occurrences where a fault resulted in tripping of and apparatus such as a transimission line, transformer, generator and so on. The device responsible for record the disturbances is called Digital Fault Recorder (DFR) and records, basically, electrical quantities as voltage and currents and also, records digital information from protection system devices. Generally, in power plants, all the DFRs data are centralized in the utility data centre and it results in an excess of data that difficults the task of analysis by the specialist engineers. This dissertation shows a new methodology for automated analysis of disturbances in power plants. A fuzzy reasoning system is proposed to deal with the data from the DFRs. The objective of the system is to help the engineer resposnible for the analysis of the DFRs’s information by means of a pre-classification of data. For that, the fuzzy system is responsible for generating unit operational state diagnosis and fault classification.

Múltiplas antenas como alternativa para aumentar a taxa de extração de chaves secretas em redes veiculares com desvanecimento lento

The communication in vehicular ad hoc networks (VANETs) is commonly divided in two scenarios, namely vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I). Aiming at establishing secure communication against eavesdroppers, recent works have proposed the exchange of secret keys based on the variation in received signal strength (RSS). However, the performance of such scheme depends on the channel variation rate, being more appropriate for scenarios where the channel varies rapidly, as is usually the case with V2V communication. In the communication V2I, the channel commonly undergoes slow fading. In this work we propose the use of multiple antennas in order to artificially generate a fast fading channel so that the extraction of secret keys out of the RSS becomes feasible in a V2I scenario. Numerical analysis shows that the proposed model can outperform, in terms of secret bit extraction rate, a frequency hopping-based method proposed in the literature.

Protocolo de roteamento para redes oportunistas utilizando otimização por enxame de partículas

In this research work, a new routing protocol for Opportunistic Networks is presented. The proposed protocol is called PSONET (PSO for Opportunistic Networks) since the proposal uses a hybrid system composed of a Particle Swarm Optimization algorithm (PSO). The main motivation for using the PSO is to take advantage of its search based on individuals and their learning adaptation. The PSONET uses the Particle Swarm Optimization technique to drive the network traffic through of a good subset of forwarders messages. The PSONET analyzes network communication conditions, detecting whether each node has sparse or dense connections and thus make better decisions about routing messages. The PSONET protocol is compared with the Epidemic and PROPHET protocols in three different scenarios of mobility: a mobility model based in activities, which simulates the everyday life of people in their work activities, leisure and rest; a mobility model based on a community of people, which simulates a group of people in their communities, which eventually will contact other people who may or may not be part of your community, to exchange information; and a random mobility pattern, which simulates a scenario divided into communities where people choose a destination at random, and based on the restriction map, move to this destination using the shortest path. The simulation results, obtained through The ONE simulator, show that in scenarios where the mobility model based on a community of people and also where the mobility model is random, the PSONET protocol achieves a higher messages delivery rate and a lower replication messages compared with the Epidemic and PROPHET protocols.