Trias Andromeda

Comparison Studies of Electrical Discharge Machining (EDM) Process Model for Low Gap Current

This paper aims to compare the material removal rate, ν between a Dimensional Analysis (DA) model, an Artificial Neural Network (ANN) model and an experimental result for a low gap current of an Electrical Discharge Machining (EDM) process. The data analysis is based on a copper electrode and steel workpiece materials. The DA and ANN model that have been developed and reported earlier by authors are used to compare the material removal of EDM process. The result indicated that the ANN model provides better accuracy towards the experimental results.

Predicting Material Removal Rate of Electrical Discharge Machining (EDM) using Artificial Neural Network for High I gap current

This article presents a prediction of Material Removal Rate (MRR) in Electrical Discharge Machining (EDM) using Artificial Neural Network (ANN). Experimental data were gathered from Die sinking EDM process for copper-electrode and steel-workpiece. It is aimed to develop a behavioral model using input-output pattern of raw data from EDM process experiment. The behavioral model is used to predict MRR and than the predicted MRR is compared to actual MRR value. The results show good agreement of predicting MRR between them.

PID controller tuning by particle swarm optimization on electrical discharge machining servo control system

Electrical Discharge Machining (EDM) is included in a stochastic process. So maintaining gap between electrode and workpiece is not easy. In order to control the gap, a proportional integral derivative (PID) controller is designed for EDM servo actuator system. The main goal of this work is to get PID parameters through Particle Swarm Optimization (PSO) algorithm to ensure a stable, robust and controlled system. The controller and the model for EDM die sinking are verified by simulation of the control system using MATLAB and simulink program. Simulation results verify the effectiveness of the PID controller in which its parameter determined by PSO to control the electrode position towards workpiece.

Erosion rate model comparison of Electrical Discharge Machining process

This paper reports a comparison studies between two erosion rate model and experimental results of an Electrical Discharge Machining (EDM) process for high gap current. Two erosion rate models are Dimensional Analysis (DA) model and Artificial Neural Network (ANN) model that have been summarized from the previous authors publication. The data analysis is based on a copper electrode and steel workpiece materials. The result indicated that the ANN model provides better accuracy than the DA model when compared to the experimental results.

Cooperative Learning for Distributed In-Network Traffic Classification

Inspired by the concept of autonomic distributed/decentralized network management schemes, we consider the issue of information exchange among distributed network nodes to network performance and promote scalability for in-network monitoring. In this paper, we propose a cooperative learning algorithm for propagation and synchronization of network information among autonomic distributed network nodes for online traffic classification. The results show that network nodes with sharing capability perform better with a higher average accuracy of 89.21% (sharing data) and 88.37% (sharing clusters) compared to 88.06% for nodes without cooperative learning capability. The overall performance indicates that cooperative learning is promising for distributed in-network traffic classification.

A prototype of multistage dynamic braking of three phase squirrel cage induction motor

This paper discussed a fast dynamic braking method of three phase induction motor. This braking method consists of two conventional braking methods i.e. direct current injection braking and capacitor self excitation braking. Those mathods were arranged in a such grading time to become a multistage dynamic braking. Simulation was done using MATLAB/Simulink software for design and predicting the behaviour. The results showed that the propossed method gave faster braking than the other two methods carried out separately.

Modeling of Flyback Converter for Micro Machining Biomedical Component

Electrical Discharge Machining is a controlled process where pulsed electrical discharge is used to erode metal in a workpiece. A number of EDM power supplies utilizing different topologies have been widely developed for various applications. Nowadays, EDM process has been given a significant amount of research focus in manufacturing micro components with new low power topologies being utilized. Recently, a demand in micro machining has also extended into biomedical applications. In this paper a current mode flyback converter is implemented for micro machining biomedical component. A MATLAB/SIMULINK modeling technique of flyback converter is presented and the effectiveness of the flyback converter topology is evaluated through the simulation results obtained by varying the value of primary inductance