Electrical and Electronics

Determination of optimum turning parameters in turning operations is one of the important tasks of process planners. The importance of this task is due to the fact that the values of turning parameters affect such objectives as turning time, turning cost and surface roughness. Thus, this problem is a multi-objective decision-making issue meaning that a parameter setting which satisfactorily achieves one of these objectives, it may not be good with respect to other objectives. Therefore, a rational compromise is to be made among these objectives. This paper determines the best cutting parameters considering relevant constraints in turning operations using a genetic algorithm coupled with an Analytic Hierarchy Process approach. The main stages of the proposed approach are two folds: (a) the non-dominated turning parameters being in the Pareto frontier are identified through a genetic algorithm, and (b) the AHP method is used to select the most suitable values for turning parameters from amongst the non-dominated solutions obtained in the first stage. Application of the proposed approach is demonstrated though an illustrative numerical example.

Regulation and controllability have been an important aspect of the industrial motor drives. The three-phase induction machine has been the motor of choice in industrial settings for about the past decade due to its easy speed and torque controllability. Its ruggedness and low cost cum other inherent features thus necessitated the quest to study its operating behavior. This work highlighted the mathematical modeling of an induction motor specifically in the stationary reference frame. The induction motor parameters and the generated equations were used to form the embedded MATLAB function which in turn was used to generate graphs that illustrate the performance of a 5HP motor. The torque –speed response among other characteristics were fully simulated thus resulting to a sound study of the performance characteristics of a three phase 5HP induction motor using MATLAB/Simulink.

As we know radium cutting through PC is readily available from that, we got the idea of our project i.e. "Low cost, thermocol cutter". In this project the microcontroller is the backbone of the hardware circuitry. All the controlling actions are done by the micro controller. A hot rod basically the soldering gun is used for cutting purpose. Here, the thermocol is not actually cut, but it is melted at a specified temperature with the help of soldering gun. So this project is used for cutting different figures and shapes as per the program of the micro controller. Optocouplers are used to provide isolation between the micro controller and the hardware circuitry. Stepper motors are used for controlling the different directions of different axis. Thickness of the thermocol will depend upon the length of the cutter and its heating capacity. Alphabets and numerical are generally cut using this project but figures of all shapes and sizes can be cut up to the limit of the work platform.

The problem of capacitor allocation in electric distribution systems involves maximizing energy and peak power loss reductions by means of capacitors installation. This paper presents a novel approach using reinforcement learning (RL) algorithm to determine suitable candidates' nodes in a distribution system for capacitor placement. The problem formulation considers two distinct objectives related to total cost of power loss and total cost of capacitors including the purchase and installation costs. The proposed method of this article uses RL for sizing and placing of capacitors in radial distribution feeders. The proposed method has been implemented in a software package and its effectiveness has been verified through a 9-bus radial distribution feeder, 34-bus radial distribution feeder along with 33-bus and 66-bus distribution systems. A comparison has been done among the proposed method of this paper and similar methods in other research works that shows the effectiveness of the proposed method of this paper for solving optimum capacitor planning problem.

The necessity of power and its dependency has grown exponentially over the years. The tremendous demand has increased the focus on minimizing power losses. One of the major problems in transmission lines is the occurrence of fault that affects the quality of electricity supply. Fault location detection is therefore the key to reliable operation of power equipments and satisfactory service delivery with minimum interruption. This need has given rise to fault location techniques so that the economic impact of fault occurrences can be mitigated with appropriate corrective measures. A numerous methods have been developed and used over the years for transmission line fault locations. This paper opts for the applicability of impedance based fault distance estimation on transmission lines. This was achieved by modelling the transmission line and simulating it using Simulink while the algorithm was written using MATLAB codes. The experimental studies indicated that this approach is reliable for rapid and correct identification of various fault locations.

The ever increasing growth in the market of PM machines has necessitated the need for a careful simulation of the performance of the very important tools capable of taking electrical study to a higher level. Simulations have helped the process of developing new systems by reducing cost and time. Simulation tools have the capabilities of performing dynamic simulations of electric machines in a graphic environment so as to ease the development of new systems. This paper investigates the performance of permanent magnet generator, with the aid of MATLAB/SIMULINK®; a powerful software mathematical tool, for high performance numerical computation. A 230V, 4hp, 2-Pole permanent magnet generator is simulated. The permanent magnets are conspicuously embedded in its rotor. The objective of the paper is to explore the response of the torque components during various operating conditions. Simulation results showed that damper resistances and rotor inertia constant affects the start-up transients of the permanent magnet generator. That is, when the damper resistance and rotor inertia constant were increased there was an increase in the start-up transients. Equally, the responses to step changes in mechanical loading were also observed.

This project proposes a real time fuzzy assisted particle swarm optimization (PSO) based energy management strategy for the multi-source electric vehicles (EVs). In pure EVs the major on-board energy source is the battery which is generally accompanied with other sources such as fuel cell (FC), ultra capacitor (UC) to improve its life time. The energy management algorithm which is formulated as an optimization problem in this project provides optimum sharing of energy sources to meet the vehicle load requirement at every instant without any prior knowledge about the driving profile. The proposed algorithm is simple, efficient and can be easily implemented in a low cost embedded system.

The ultimate goal of the deployment of any voice-centric application is to provide a natural way of human-machine interaction in end-to-end communication and majority of the voice-centric applications in today’s world are promising the same. In this scenario, it is essential to investigate the performance of Speech-Enabled IVR (SEIVR) under the effect of different narrowband codecs. In this paper, the performance of SEIVR has been analyzed by utilizing an ASR engine and speech codecs. SPHNIX-3 has been used as the ASR engine which is CMU’s ASR toolkit for speech recognition and executable files of various narrowband codec are generated with the help of source code and it is taken from standard organizations such as ITU-T, ETSI and ISO/IEC. The results of this paper are completely based on the speech data from TIMIT speech database. The major work done in this paper is to prove that the recognition accuracy of SEIVR increases when there is an increase in Gaussian mixture from Context-Independent (CI) to Context-Dependent (CD) under the influence of various narrow band codecs.

This paper evaluates the benefits of operating an electric distribution network in a security-constrained optimal power flow (SCOPF) in order to mitigate against possible blackout in an N-1 contingency. A 16-bus UKGDS network was used for the analysis. An SCOPF was performed on the network by introducing N-1 line contingency to the network and this resulted to constraints violations. The infeasibility in the solution occurred due to the radial nature of the network. The operation of SCOPF is realized in a mesh network system, which was done by connecting branches between bus 5-7 and bus 12-16 to the network. The system was simulated to operate in SCOPF and N-1 line contingency was inserted to the network to test for constraint violation/ feasibility of the system. This resulted in feasible solution in all the line contingencies with no constraint violation.

Cryptography circuits for portable electronic devices provide user authentication and secure data communication. These circuits should, in general, occupy small chip area, consume low power, handle several cryptography algorithms, and provide acceptable performance. This paper presents the simulation and synthesis of three standard cryptography algorithms on a universal architecture. The cryptography processor implements both private key and public key algorithms and meets the power and performance specifications. The mentor graphics modelsim tool is used for design and simulation and also Synopsys Design Compiler tool is used for synthesis. TSMC 65nm library is used for the synthesis.