Gerenciamento de Big Data em plantas industriais

Nowadays the companies generate great amount of data from different sources, however some of them produce more data than they can analyze. Big Data is a set of data that grows very fast, collected several times during a short period of time. This work focus on the importance of the correct management of Big Data in an industrial plant. Through a case study based on a company that belongs to the pulp and paper area, the problems resolutions are going to be presented with the usage of appropriate data management. In the final chapters, the results achieved by the company are discussed, showing how the correct choice of data to be monitored and analyzed brought benefits to the company, also best practices will be recommended for the Big Data management

Localizador de faltas por ondas viajantes em linhas de transmissão

It is important to ensure smoothly operation of a transmission line, sending energy to the consumption centers with minimal interruptions and safer. With this necessity, the fault location techniques have grown, in order to mitigate the impact of the fault and its correction can be more quickly and accurately. This paper presents a comparison between two different techniques of fault location, the fault location by impedance method, which uses the line parameters, the impedance per distance, voltage and current signals, and the other is the traveling wave method, which uses only a very fast analysis of time, synchronization and length between the line ends, do not using voltage and current values, but the temporal perception of the fault. Using travelling waves fault detection makes the previous knowledge of line parameters obsolete, which helps a lot network technicians and engineers with a quick and easy analysis. The methods are simulated in ATP Draw software, so both algorithms can be evaluated for their effectively and accuracy