Recovery Tests of an Hybrid Current Limiter Composed of a SFCL in Parallel to an Air-Core Power Reactor

The resistive-type superconducting fault current limiters (RSFCL) prototypes using YBCO-coated conductors have shown current limitation for medium voltage class applications for acting time up to 80 ms. By connecting an air-core reactor in parallel with the RSFCL, thus making an hybrid current limiter, one can extend the acting time for up to 1 s. In this work, we report the performance of a hybrid current limiter subjected to an AC peak fault current of 2 kA during 1 s for which within the first 80 ms the SFCL limits the current concurrently with the air-core reactor, and for the remaining 920 ms, only the air-core reactor limits the current. In order to evaluate the actual conditions for subsequent reconnection of RSFCL to the power grid, the hybrid fault current limiter was tested varying the time interval for recovery from 900 ms and 1.2 s, followed again by the concurrent operation of the hybrid limiter during 1 s (SFCL during 80 ms). From this evaluation test, the recovery time can be measured and compared using the voltage peak generated in superconducting module from the first and second fault test. The recovery time was also determined through the pulsed current method (PCM) on short-length sample test. The results showed that the fault current was limited from 1.9 kA down to 514 A after 1 cycle of 60 Hz frequency, with recovery time lower than 1.2 s for two subsequent fault current tests.

Learning kernels for support vector machines with polynomial powers of sigmoid

In the pattern recognition research field, Support Vector Machines (SVM) have been an effectiveness tool for classification purposes, being successively employed in many applications. The SVM input data is transformed into a high dimensional space using some kernel functions where linear separation is more likely. However, there are some computational drawbacks associated to SVM. One of them is the computational burden required to find out the more adequate parameters for the kernel mapping considering each non-linearly separable input data space, which reflects the performance of SVM. This paper introduces the Polynomial Powers of Sigmoid for SVM kernel mapping, and it shows their advantages over well-known kernel functions using real and synthetic datasets.

Instantaneous complex power applied to three-phase machines

The theory presented in this paper was primarily developed to give a physical interpretation for the instantaneous power flow on a three-phase induction machine, without a neutral conductor, on any operational state and may be extended to any three-phase load. It is a vectorial interpretation of the instantaneous reactive power theory presented by Akagi et al. Which, believe the authors, isn't enough developed and its physical meaning not yet completely understood. This vectorial interpretation is based on the instantaneous complex power concept defined by Torrens for single-phase, ac, steady-state circuits, and leads to a better understanding of the power phenomenon, particularly of the distortion power. This concept has been extended by the authors to three-phase systems, through the utilization of the instantaneous space vectors. The results of measurements of instantaneous complex power on a self-excited induction generator's terminals, during an over-load application transient, are presented for illustration. The compensation of reactive power proposed by Akagi is discussed and a new horizon for the theory application is opened.

Expert system to detect incipient fauts in rotating machines using fuzzy logic and virtual instrumentation

This paper refers to the design of an expert system that captures a waveform through the use of an accelerometer, processes the signal and converts it to the frequency domain using a Fast Fourier Transformer to then, using artificial intelligence techniques, specifically Fuzzy Reasoning, it determines if there is any failure present in the underlying mode of the equipment, such as imbalance, misalignment or bearing defects.

Model selection for discriminative restricted boltzmann machines through meta-heuristic techniques

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)