T. Sree Renga Raja

Harmonic elimination by Shunt active filter using PI controller

This paper deals with an innovating Shunt active filter with PI controller for harmonic elimination. Active filter provide a viable solution to mitigating harmonic issues caused by the non linear loads. The active filter compensates the reactive and harmonic currents drawn by the non-linear loads besides power factor correction. The objective is to study different control strategies for real time compensating current. PI controller reduces the ripple voltage of DC capacitor of Pulse width modulated voltage source inverter. The switching angles can be determined using PI controller to suppress the harmonics. It is shown through simulation that the proposed active filter can achieve high overall system performance.

Investigations on Eco Friendly Insulating Fluids from Rapeseed and Pongamia Pinnata Oils for Power Transformer Applications

Transformer mineral oil which is normally hydrocarbon based is non- biodegradable and pollutes the environment in all aspects. Though vegetable oils are eco-friendly in nature and potentially could be used in transformers as a replacement for the mineral oil, there usage is restricted because of their oxidative instability. The present work focuses on using rapeseed oil and pongamia (pongamia pinnata) oil as effective alternatives for the traditional mineral oil in power transformer. The oxidative stability of the rapeseed oil and pongamia oil is increased by using combinations of the natural and synthetic anti-oxidants as additives. The parameters like breakdown voltage, viscosity, flash point, fire point are measured for the rapeseed oil and pongamia oil with and without the additives as per IEC and ASTM standards. The results shown encouraging changes in the parameter values and ensures the use of the oils as a potential alternative insulation in power transformers.

Impact of applying pre-processing techniques for improving classification accuracy

Image denoising is a procedure aimed at removing noise from images while retaining as many important signal features as possible. Many images suffer from poor contrast due to inadequate illumination or finite sensitivity of the imaging device, electronic sensor noise or atmospheric disturbances. This paper proposes a hybrid directional lifting technique for image denoising to retain the original information present in the images. The primary objective of this paper is to show the impact of applying preprocessing techniques for improving classification accuracy. In order to classify the image accurately, effective preservation of edges and contour details of an image is essential. The discrete wavelet transform-based interpolation technique is developed for resolution enhancement. The image is then classified using support vector machine classifier, which is well suitable for image classification. The efficiency of the classifier is analyzed based on receiver operating characteristic (ROC) curves. The quantitative performance measures peak signal to noise ratio and ROC analysis show the significance of the proposed techniques.

An intelligent biological inspired evolutionary algorithm for the suppression of incubator interference in premature infants ECG

Electromagnetic interference produced by the incubator medical equipments may interrupt or degrade the premature infant’s electrocardiography (ECG) signal. The premature infant’s ECG is usually contaminated by an interference caused by the incubator devices. The interference cancellation system is designed using an adaptive learning ability of artificial neural network Levenberg–Marquardt (LM) algorithm. In this paper the swarm intelligent-LM algorithm is used for the electromagnetic interference cancellation in infant ECG signal. The swarm intelligent algorithm is used for the optimization by selecting the optimized number of neurons in the hidden layer, learning rate and momentum factor of the neural network. Also, this paper presents a comparison of residual mean square error (RMSE) values for neural network trained by LM algorithm, hybrid genetic-LM algorithm and hybrid swarm intelligent-LM algorithm. The LM algorithm is used for the weight updating and reducing the content of electromagnetic interference noise present in the signal. The performance analysis of the proposed noise cancellation approach is compared with gradient based and evolutionary based algorithms. The result analysis shows that the interferences in infant ECG signal is removed successfully using the proposed approach.

Deterioration of solid insulation for thermal degradation of transformer oil

Power transformers are the most vital components of power system. Insulation used in power transformers are of insulating fluids and solid insulation system like pressboard, Kraft paper. In this work an effort has been made to investigate the detoriation of solid insulation systems for thermal degradation of transformer oil. The aging degree of solid insulation system is examined through Atomic force Microscope (AFM), Scanning Electron Microscope (SEM) and X-ray diffraction (XRD) techniques.

NOVEL COLOR FILTER ARRAY DEMOSAICING IN FREQUENCY DOMAIN WITH SPATIAL REFINEMENT

The main idea behind wavelet based demosaicing with spatial refinement is to reconstruct the full reso lution color image from the mosaiced image. In this study, a new effective wavelet based demosaicing algorith m for interpolating the missing color components in Bayer ’s Color Filter Array (CFA) pattern is proposed. Th is interpolation technique uses the interchannel corre lation among the high frequency subbands to determine the missing pixels in each color channel, followed by a refining step in spatial domain which uses non-ite rative technique that enforces color difference rule with fewer computations. As a result, the proposed demosaicing method yields better performance than bilinear, edg e based and subband based demosaicing methods.

Implementation of Robust Prediction Observer Controller for DC-DC Converter

A discrete controller is designed for low power dc-dc switched mode power supplies. The approach is based on time domain and the control loop continuously and concurrently tunes the compensator parameters to meet the converter specifications. A digital state feedback control combined with the load estimator provides a complete compensation, which further improves the dynamic performance of the closed loop system. Simulation of digitally controlled Buck converter is performed with MATLAB/Simulink. Experimental results are given to demonstrate the effectiveness of the controller using LabVIEW with a data acquisition card (model DAQ Pad - 6009).

Time Domain Based Digital Controller for Sepic Converter

This paper presents a discrete PWM controller for SEPIC (Single ended Primary Inductor Converter) converter. SEPIC is chosen since it has positive voltage gain and higher characteristics than any other converter. To improve the transient response and dynamic stability of the proposed converter, Discrete PID controller is the most preferable one. The proposed controller improves the dynamic performance of the SEPIC converter by achieving a robust output voltage against load disturbances, input voltage variations and changes in circuit components. The converter is designed through simulation using MATLAB / Simulink and performance parameters are also measured. The discrete controller is implemented, design goal is achieved and the same is verified against theoretical calculation using LabVIEW. Keywords: SEPIC converter, Discrete PID Controller, Analog to Digital Converter (ADC), Digital Pulse Width Modulator (DPWM).

Application of particle swarm optimization for auction based dispatch in deregulated environment

This paper presents an intuitive solution to the auction based dispatch problem in the deregulated power system based on swarm intelligence optimization. The formulated expressions effectively substitute the sellers bidden cost function in the production cost including market strategy. The auction methodology for maximum thermal capacity of every line of the system is completed using the calculated values of power flows in each line and Locational Marginal Price (LMP). The cost of transmitting a specific amount of electrical power through each line is calculated through auction (in MW) and substituted in the same system to minimize the production cost of generators through particle swarm optimization (PSO) algorithm with satisfying constraints like balance of supply, demand constraint and the capacity limit. Triumph of the developed algorithm is demonstrated using two test systems (3 sellers and 8 sellers). Detailed results such as the cost convergence characteristics, parameter selection for PSO algorithm and sellers contracted demands illustrate the competent performance and merits of the proposed algorithm.