An intelligent approach using support vector machines for monitoring and identification of faults on transmission systems

Power system disturbances are often caused by faults on transmission lines. When faults occur in a power system, the protective relays detect the fault and initiate tripping of appropriate circuit breakers, which isolate the affected part from the rest of the power system. Generally Extra High Voltage (EHV) transmission substations in power systems are connected with multiple transmission lines to neighboring substations. In some cases mal-operation of relays can happen under varying operating conditions, because of inappropriate coordination of relay settings. Due to these actions the power system margins for contingencies are decreasing. Hence, power system protective relaying reliability becomes increasingly important. In this paper an approach is presented using Support Vector Machine (SVM) as an intelligent tool for identifying the faulted line that is emanating from a substation and finding the distance from the substation. Results on 24-bus equivalent EHV system, part of Indian southern grid, are presented for illustration purpose. This approach is particularly important to avoid mal-operation of relays following a disturbance in the neighboring line connected to the same substation and assuring secure operation of the power systems.

Cluster based core vector machine

Core Vector Machine(CVM) is suitable for efficient large-scale pattern classification. In this paper, a method for improving the performance of CVM with Gaussian kernel function irrespective of the orderings of patterns belonging to different classes within the data set is proposed. This method employs a selective sampling based training of CVM using a novel kernel based scalable hierarchical clustering algorithm. Empirical studies made on synthetic and real world data sets show that the proposed strategy performs well on large data sets.

Computing complete test graphs for hierarchical systems

Conformance testing focuses on checking whether an implementation. under test (IUT) behaves according to its specification. Typically, testers are interested it? performing targeted tests that exercise certain features of the IUT This intention is formalized as a test purpose. The tester needs a "strategy" to reach the goal specified by the test purpose. Also, for a particular test case, the strategy should tell the tester whether the IUT has passed, failed. or deviated front the test purpose. In [8] Jeron and Morel show how to compute, for a given finite state machine specification and a test purpose automaton, a complete test graph (CTG) which represents all test strategies. In this paper; we consider the case when the specification is a hierarchical state machine and show how to compute a hierarchical CTG which preserves the hierarchical structure of the specification. We also propose an algorithm for an online test oracle which avoids a space overhead associated with the CTG.

Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network

In this paper. we propose a novel method using wavelets as input to neural network self-organizing maps and support vector machine for classification of magnetic resonance (MR) images of the human brain. The proposed method classifies MR brain images as either normal or abnormal. We have tested the proposed approach using a dataset of 52 MR brain images. Good classification percentage of more than 94% was achieved using the neural network self-organizing maps (SOM) and 98% front support vector machine. We observed that the classification rate is high for a Support vector machine classifier compared to self-organizing map-based approach.

Scalable non-linear Support Vector Machine using hierarchical clustering

This paper discusses a method for scaling SVM with Gaussian kernel function to handle large data sets by using a selective sampling strategy for the training set. It employs a scalable hierarchical clustering algorithm to construct cluster indexing structures of the training data in the kernel induced feature space. These are then used for selective sampling of the training data for SVM to impart scalability to the training process. Empirical studies made on real world data sets show that the proposed strategy performs well on large data sets.

Dielectric and dc electrical studies of antiferroelectric lead zirconate thin films

Antiferroelectric lead zirconate thin films were deposited using KrF (248 nm) excimer laser ablation technique. Utilization of antiferroelectric materials is proposed in high charge storage capacitors and microelectromechanical (MEMs) devices. The antiferroelectric nature of lead zirconate thin films was confirmed by the presence of double hysteresis behavior in polarization versus applied field response. By controlling the processing parameters, two types of microstructures evolved, namely columnar (or in-situ) and multi-grained (or ex-situ) in PZ thin films. The dielectric and electrical properties of the lead zirconate thin films were studied with respect to the processing parameters. Analysis on charge transport mechanism, using space charge limited conduction phenomenon, showed the presence of both shallow and deep trap sites in the PZ thin films. The estimated shallow trap energies were 0.448 and 0.491 eV for in-situ and ex-situ films, with respective concentrations of approximate to 7.9 x 10(18)/cc and approximate to 2.97 x 10(18)/cc. The deep trap energies with concentrations were 1.83 eV with 1.4 x 10(16)/cc for ex-situ and 1.76 eV with 3.8 x 10(16)/cc for in-situ PZ thin films, respectively. These activation energies were found to be consistent with the analysis from Arrhenius plots of de current densities. (C) 2000 Elsevier Science S.A. All rights reserved.

Temperature and pressure dependence of direct current electrical resistivity in the Na2O-ZnO-B2O3 glass system

Two series of glasses were prepared, xNa2O, yZnO, 100 - x - yB2O3 and 30 - xNa2O, xZnO, 70B2O3 (mol%). The temperature dependence of the direct current resistivity was measured from room temperature to about 700 K and in both series of glasses we observed a simple Arrhenius type of temperature dependence. However, the resistivity of the binary alkali glass increased steeply by as much as two orders of magnitude with the addition of even a small quantity of ZnO and remained virtually unaffected by further addition of ZnO. The resistivity decreases gradually with increasing pressure in Na2O-B2O3 but increases with increasing pressure with the addition of ZnO.

Synthesis, magnetic and electrical properties of Fe-containing SiO2 nanocomposite

Nanocrystalline Fe powders were synthesized by transmetallation reaction and embedded in silica to form Fe-SiO2 nanocomposite. Thermomagnetic study of the as-prepared Fe sample indicates the presence of Fe3O4 and Fe particles. Oxidation studies of Fe and Fe-SiO2 show an increased thermal stability of Fe-SiO2 nanocomposite over pure Fe. The Fe-SiO2 shows an enhanced oxidation temperature (i.e., 780 K) and a maximum saturation magnetization value of (135 emu/g) with 64 wt.% of Fe content in silica. Electrical and dielectric behaviour of the Fe-SiO2 nanocomposite has been investigated as a function of temperature and frequency. Low frequency ac conductivity and dielectric constants were found to be influenced by desorptions of chemisorbed moisture. High saturation magnetization, thermal stability, frequency-dependent conductivity and low power loss make Fe-silica a promising material for high frequency applications. (C) 2010 Elsevier B.V. All rights reserved.

Electrical and Dielectric Behaviour at the Critical Point of Binary Liquids: Acetonitrile + Cyclohexane

The electrical capacitance and resistance of the binary liquid mixture cyclohexane + acetonitrile are measured in the one phase and two phase regions at spot frequencies between 5 kHz and 100 kHz. This sample has a very low gravity affected (∼0.6 mK) region. In one phase region the capacitance data show a sharp, ∼0.7% increase above background within 0.5 degrees of Tc whereas the resistance has a smooth increase of ∼1.5% above background in a (T−Tc) range of 4 degrees. Two phase values of capacitance and resistance from the coexisting phases are used to determine the critical parameters Tc (critical temperature), Rc (resistance at Tc) and Cc (capacitance at Tc). A precise knowledge of these parameters reduces the uncertainty on the critical exponent 0 for C and R. The one phase capacitance data fit to an (1 - α) exponent in a limited temperature range of 0.2 degrees. Resistance data strongly support an (1 - α) exponent over the entire 5 degree range.

Isobaric electrical resistance along the critical line in nickel: An experimental test of universality

High-precision measurement of the electrical resistance of nickel along its critical line, a first attempt of this kind, as a function of pressure to 47.5 kbar is reported. Our analysis yields the values of the critical exponents α=α’=-0.115±0.005 and the amplitude ratios ‖A/A’‖=1.17±0.07 and ‖D/D’‖=1.2±0.1. These values are in close agreement with those predicted by renormalization-group (RG) theory. Moreover, this investigation provides an unambiguous experimental verification to one of the key consequences of RG theory that the critical exponents and amplitudes ratios are insensitive to pressure variation in nickel, a Heisenberg ferromagnet.

A comparative study of the magnetic and electrical properties of perovskite oxides and the corresponding two-dimensional oxides of K2NiF4

Electrical and magnetic properties of several oxide systems of K2NiF4 structure have been compared to those of the corresponding perovskites. Members of the La1−xSr1+xCoO4 system are all semiconductors with a high activation energy for conduction unlike La1−xSrxCoO3 (x ≥ 0.3) which is metallic; the latter oxides are ferromagnetic. La0.5Sr1.5CoO4 shows a magnetization of 0.5 μB at 0 K (compared to 1.5 μB of La0.5Sr0.5CoO3), but the high-temperature susceptibilities of the two systems are comparable. In SrO · (La0.5Sr0.5MnO3)n, both magnetization and electrical conductivity increase with the increase in n approaching the value of the perovskite La0.5Sr0.5MnO3. LaSrMn0.5Ni0.5(Co0.5)O4 shows no evidence of long-range ferromagnetic ordering unlike the perovskite LaMn0.5Ni0.5(Co0.5)O3; high-temperature susceptibility behavior of these two insulating systems is, however, similar. LaSr1−xBaxNiO4 exhibits high electrical resistivity with the resistivity increasing proportionately with the magnetic susceptibility (note that LaNiO3 is a Pauli-paramagnetic metal). High-temperature susceptibility of LaSrNiO4 and LaNiO3 are comparable. Susceptibility measurements show no evidence for long-range ordering in LaSrFe1−xNixO4 unlike in LaFe1−xNixO3 (x ≤ 0.35) and the electrical resistivity of the former is considerably higher. Electrical resistivity of Sr2RuO4 is more than an order of magnitude higher than that of SrRuO3. Some generalizations of the properties of two- and three-dimensional oxide systems have emerged from these experimental observations.

Analysis of effects of ambients (temperature and light intensity) on the electrical breakdown in bipolar transistors

This paper presents an analysis of the effects of ambients-temperature and light intensity on the V-l characteristics of bipolar transistors under electrical breakdown. The analysis is based on the transportation and storage of majority carriers in the base region. It is shown that this analysis can explain the observed shift in the V-l characteristics to lower voltages with increase in either temperature or light intensity.