Knowledge-Based Approach Using Support Vector Machine for Transmission Line Distance Relay Co-ordination

In this paper, knowledge-based approach using Support Vector Machines (SVMs) are used for estimating the coordinated zonal settings of a distance relay. The approach depends on the detailed simulation studies of apparent impedance loci as seen by distance relay during disturbance, considering various operating conditions including fault resistance. In a distance relay, the impedance loci given at the relay location is obtained from extensive transient stability studies. SVMs are used as a pattern classifier for obtaining distance relay co-ordination. The scheme utilizes the apparent impedance values observed during a fault as inputs. An improved performance with the use of SVMs, keeping the reach when faced with different fault conditions as well as system power flow changes, are illustrated with an equivalent 265 bus system of a practical Indian Western Grid.

Surface electrode switching of a 16-electrode wireless EIT system using RF-based digital data transmission scheme with 8 channel encoder/decoder ICs

A Radio Frequency (RF) based digital data transmission scheme with 8 channel encoder/decoder ICs is proposed for surface electrode switching of a 16-electrode wireless Electrical Impedance Tomography (EIT) system. A RF based wireless digital data transmission module (WDDTM) is developed and the electrode switching of a EIT system is studied by analyzing the boundary data collected and the resistivity images of practical phantoms. An analog multiplexers based electrode switching module (ESM) is developed with analog multiplexers and switched with parallel digital data transmitted by a wireless transmitter/receiver (T-x/R-x) module working with radio frequency technology. Parallel digital bits are generated using NI USB 6251 card working in LabVIEW platform and sent to transmission module to transmit the digital data to the receiver end. The transmitter/receiver module developed is properly interfaced with the personal computer (PC) and practical phantoms through the ESM and USB based DAQ system respectively. It is observed that the digital bits required for multiplexer operation are sequentially generated by the digital output (D/O) ports of the DAQ card. Parallel to serial and serial to parallel conversion of digital data are suitably done by encoder and decoder ICs. Wireless digital data transmission module successfully transmitted and received the parallel data required for switching the current and voltage electrodes wirelessly. 1 mA, 50 kHz sinusoidal constant current is injected at the phantom boundary using common ground current injection protocol and the boundary potentials developed at the voltage electrodes are measured. Resistivity images of the practical phantoms are reconstructed from boundary data using EIDORS. Boundary data and the resistivity images reconstructed from the surface potentials are studied to assess the wireless digital data transmission system. Boundary data profiles of the practical phantom with different configurations show that the multiplexers are operating in the required sequence for common ground current injection protocol. The voltage peaks obtained at the proper positions in the boundary data profiles proved the sequential operation of multiplexers and successful wireless transmission of digital bits. Reconstructed images and their image parameters proved that the boundary data are successfully acquired by the DAQ system which in turn again indicates a sequential and proper operation of multiplexers as well as the successful wireless transmission of digital bits. Hence the developed RF based wireless digital data transmission module (WDDTM) is found suitable for transmitting digital bits required for electrode switching in wireless EIT data acquisition system. (C) 2011 Elsevier Ltd. All rights reserved.

On-Chip Memory Architecture Exploration Framework for DSP Processor-Based Embedded System on Chip

Today's SoCs are complex designs with multiple embedded processors, memory subsystems, and application specific peripherals. The memory architecture of embedded SoCs strongly influences the power and performance of the entire system. Further, the memory subsystem constitutes a major part (typically up to 70%) of the silicon area for the current day SoC. In this article, we address the on-chip memory architecture exploration for DSP processors which are organized as multiple memory banks, where banks can be single/dual ported with non-uniform bank sizes. In this paper we propose two different methods for physical memory architecture exploration and identify the strengths and applicability of these methods in a systematic way. Both methods address the memory architecture exploration for a given target application by considering the application's data access characteristics and generates a set of Pareto-optimal design points that are interesting from a power, performance and VLSI area perspective. To the best of our knowledge, this is the first comprehensive work on memory space exploration at physical memory level that integrates data layout and memory exploration to address the system objectives from both hardware design and application software development perspective. Further we propose an automatic framework that explores the design space identifying 100's of Pareto-optimal design points within a few hours of running on a standard desktop configuration.

A Chemodosimetric Probe Based on a Conjugated Oxidized Bis-Indolyl System for Selective Naked-Eye Sensing of Cyanide Ions in Water

A new bis-indolyl-based colorimetric probe has been synthesized. This allows a Michael-type adduct formation for the detection of cyanide ions. The probe shows a remarkable color change from red to colorless upon addition of the cyanide ions in pure water. The cyanide ion reacts with the probe and removes the conjugation of the bis-indolyl moiety of the probe with that of the 4-substituted aromatic ring. This renders the probe colorless. The mechanism of the reaction of the probe with the cyanide ion was established by using 1H and 13C NMR spectroscopy, mass spectrometry, and kinetic studies.

Arithmetic coding based lossless compression schemes for power system steady state operational data

Introduction of processor based instruments in power systems is resulting in the rapid growth of the measured data volume. The present practice in most of the utilities is to store only some of the important data in a retrievable fashion for a limited period. Subsequently even this data is either deleted or stored in some back up devices. The investigations presented here explore the application of lossless data compression techniques for the purpose of archiving all the operational data - so that they can be put to more effective use. Four arithmetic coding methods suitably modified for handling power system steady state operational data are proposed here. The performance of the proposed methods are evaluated using actual data pertaining to the Southern Regional Grid of India. (C) 2012 Elsevier Ltd. All rights reserved.

Switching of a Sixteen Electrode Array for Wireless EIT System Using a RF-Based 8-Bit Digital Data Transmission Technique

Surface electrode switching of 16-electrode wireless EIT is studied using a Radio Frequency (RF) based digital data transmission technique operating with 8 channel encoder/decoder ICs. An electrode switching module is developed the analog multiplexers and switched with 8-bit parallel digital data transferred by transmitter/receiver module developed with radio frequency technology. 8-bit parallel digital data collected from the receiver module are converted to 16-bit digital data by using binary adder circuits and then used for switching the electrodes in opposite current injection protocol. 8-bit parallel digital data are generated using NI USB 6251 DAQ card in LabVIEW software and sent to the transmission module which transmits the digital data bits to the receiver end. Receiver module supplies the parallel digital bits to the binary adder circuits and adder circuit outputs are fed to the multiplexers of the electrode switching module for surface electrode switching. 1 mA, 50 kHz sinusoidal constant current is injected at the phantom boundary using opposite current injection protocol. The boundary potentials developed at the voltage electrodes are measured and studied to assess the wireless data transmission.

A Hybrid Multilevel Inverter System Based on Dodecagonal Space Vectors for Medium Voltage IM Drives

Dodecagonal (12-sided) space vector pulsewidth modulation (PWM) schemes are characterized by the complete absence of (6n +/- 1)th-order harmonics (for odd n) in the phase voltages, within the linear modulation range and beyond, including over-modulation. This paper presents a new topology suitable for the realization of such multilevel inverter schemes for induction motor (IM) drives, by cascading two-level inverters with flying-capacitor-inverter fed floating H-bridge cells. Now, any standard IM may be used to get the dodecagonal operation which hitherto was possible only with open-end winding IM. To minimize the current total harmonic distortion (THD), a strategy for synchronous PWM is also proposed. It is shown that the proposed method is capable of obtaining better THD figures, compared to conventional dodecagonal schemes. The topology and the PWM strategy are validated through analysis and subsequently verified experimentally.

A weight based context analysis system to provide a required UMM service

Ubiquitous Computing is an emerging paradigm which facilitates user to access preferred services, wherever they are, whenever they want, and the way they need, with zero administration. While moving from one place to another the user does not need to specify and configure their surrounding environment, the system initiates necessary adaptation by itself to cope up with the changing environment. In this paper we propose a system to provide context-aware ubiquitous multimedia services, without user’s intervention. We analyze the context of the user based on weights, identify the UMMS (Ubiquitous Multimedia Service) based on the collected context information and user profile, search for the optimal server to provide the required service, then adapts the service according to user’s local environment and preferences, etc. The experiment conducted several times with different context parameters, their weights and various preferences for a user. The results are quite encouraging.

Strain localization effect on system reliability based design of bridge abutments under earthquake loading

The component and system reliability based design of bridge abutments under earthquake loading is presented in the paper. Planar failure surface has been used in conjunction with pseudo-dynamic approach to compute seismic active earth pressures on an abutment. The pseudo-dynamic method, considers the effect of phase difference in shear waves, soil amplification along with the horizontal seismic accelerations, strain localization in backfill soil and associated post-peak reduction in the shear resistance from peak to residual values along a previously formed failure plane. Four modes of stability viz. sliding, overturning, eccentricity and bearing capacity of the foundation soil are considered in the analysis. The series system reliability is computed with an assumption of independent failure modes. The lower and upper bounds of system reliability are also computed by taking into account the correlations between four failure modes, which is evaluated using the direction cosines of the tangent planes at the most probable points of failure.

Support vector machine based high speed protection relay for EHV/UHV transmission line

This paper presents a fast and accurate relaying technique for a long 765kv UHV transmission line based on support vector machine. For a long EHV/UHV transmission line with large distributed capacitance, a traditional distance relay which uses a lumped parameter model of the transmission line can cause malfunction of the relay. With a frequency of 1kHz, 1/4th cycle of instantaneous values of currents and voltages of all phases at the relying end are fed to Support Vector Machine(SVM). The SVM detects fault type accurately using 3 milliseconds of post-fault data and reduces the fault clearing time which improves the system stability and power transfer capability. The performance of relaying scheme has been checked with a typical 765kV Indian transmission System which is simulated using the Electromagnetic Transients Program(EMTP) developed by authors in which the distributed parameter line model is used. More than 15,000 different short circuit fault cases are simulated by varying fault location, fault impedance, fault incidence angle and fault type to train the SVM for high speed accurate relaying. Simulation studies have shown that the proposed relay provides fast and accurate protection irrespective of fault location, fault impedance, incidence time of fault and fault type. And also the proposed scheme can be used as augmentation for the existing relaying, particularly for Zone-2, Zone-3 protection.

Inference for the Component and System Lifetime Distribution of a k-unit Parallel System Based on System Data

In this paper, we consider the inference for the component and system lifetime distribution of a k-unit parallel system with independent components based on system data. The components are assumed to have identical Weibull distribution. We obtain the maximum likelihood estimates of the unknown parameters based on system data. The Fisher information matrix has been derived. We propose -expectation tolerance interval and -content -level tolerance interval for the life distribution of the system. Performance of the estimators and tolerance intervals is investigated via simulation study. A simulated dataset is analyzed for illustration.

Design and Evaluation of a Robust Optical Beam-Interruption-Based Vehicle Classifier System

This paper presents the design and development of a novel optical vehicle classifier system, which is based on interruption of laser beams, that is suitable for use in places with poor transportation infrastructure. The system can estimate the speed, axle count, wheelbase, tire diameter, and the lane of motion of a vehicle. The design of the system eliminates the need for careful optical alignment, whereas the proposed estimation strategies render the estimates insensitive to angular mounting errors and to unevenness of the road. Strategies to estimate vehicular parameters are described along with the optimization of the geometry of the system to minimize estimation errors due to quantization. The system is subsequently fabricated, and the proposed features of the system are experimentally demonstrated. The relative errors in the estimation of velocity and tire diameter are shown to be within 0.5% and to change by less than 17% for angular mounting errors up to 30 degrees. In the field, the classifier demonstrates accuracy better than 97.5% and 94%, respectively, in the estimation of the wheelbase and lane of motion and can classify vehicles with an average accuracy of over 89.5%.

Support vector clustering-based direct coherency identification of generators in a multi-machine power system

This study investigates the application of support vector clustering (SVC) for the direct identification of coherent synchronous generators in large interconnected multi-machine power systems. The clustering is based on coherency measure, which indicates the degree of coherency between any pair of generators. The proposed SVC algorithm processes the coherency measure matrix that is formulated using the generator rotor measurements to cluster the coherent generators. The proposed approach is demonstrated on IEEE 10 generator 39-bus system and an equivalent 35 generators, 246-bus system of practical Indian southern grid. The effect of number of data samples and fault locations are also examined for determining the accuracy of the proposed approach. An extended comparison with other clustering techniques is also included, to show the effectiveness of the proposed approach in grouping the data into coherent groups of generators. This effectiveness of the coherent clusters obtained with the proposed approach is compared in terms of a set of clustering validity indicators and in terms of statistical assessment that is based on the coherency degree of a generator pair.

Purifying water containing both anionic and cationic species using a (Zn, Cu)O, ZnO, and Cobalt Ferrite based multiphase adsorbent system

For the purpose of water purification, novel and low-cost adsorbents which are promising replacements for activated carbon are being actively pursued. However, a single-phase material that adsorbs both cationic and anionic species remains elusive. Hence, a low-cost, multiphase adsorbent bed that purifies water containing both anionic and cationic pollutants is a desirable alternative. We choose anionic (Congo red, Orange G) and cationic (methylene blue, malachite green) dyes as model pollutants. These dyes are chosen since they are widely found in effluents from textile, leather, fishery, and pharmaceutical industries, and their carcinogenic, mutagenic, genotoxic, and cytotoxic impact on mammalian cells is well-established. We show that ZnO, (Zn0.24Cu0.76)O and cobalt ferrite based multiphase fixed adsorbent bed efficiently adsorbs model anionic (Congo red, Orange G) and cationic (methylene blue and malachite green) pollutants, and their complex mixtures. All adsorbent phases are synthesized using room-temperature, high-yield (similar to 96-100%), green chemical processes. The nanoadsorbents are characterized by using X-ray powder diffraction (XRD), scanning electron microscopy (SEM), Brunauer-Emmett-Teller (BET) surface area analysis, and zeta potential measurements. The constituent nanophases are deliberately chosen to be beyond 50 nm, in order to avoid the nanotoxic size regime of oxides. Adsorption characteristics of each of the phases are examined. Isotherm based analysis shows that adsorption is both spontaneous and highly favorable. zeta potential measurements indicate that electrostatic interactions are the primary driving force for the observed adsorption behavior. The isotherms obtained are best described using a composite Langmuir-Freundlich model. Pseudo-first-order, rapid kinetics is observed (with adsorption rate constants as high as 0.1-0.2 min(-1) in some cases). Film diffusion is shown to be the primary mechanism of adsorption.

A scaled unscented transformation based directed Gaussian sum filter for nonlinear dynamic system identification

Impoverishment of particles, i.e. the discretely simulated sample paths of the process dynamics, poses a major obstacle in employing the particle filters for large dimensional nonlinear system identification. A known route of alleviating this impoverishment, i.e. of using an exponentially increasing ensemble size vis-a-vis the system dimension, remains computationally infeasible in most cases of practical importance. In this work, we explore the possibility of unscented transformation on Gaussian random variables, as incorporated within a scaled Gaussian sum stochastic filter, as a means of applying the nonlinear stochastic filtering theory to higher dimensional structural system identification problems. As an additional strategy to reconcile the evolving process dynamics with the observation history, the proposed filtering scheme also modifies the process model via the incorporation of gain-weighted innovation terms. The reported numerical work on the identification of structural dynamic models of dimension up to 100 is indicative of the potential of the proposed filter in realizing the stated aim of successfully treating relatively larger dimensional filtering problems. (C) 2013 Elsevier Ltd. All rights reserved.