Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Computer Science
Firas Saaduldeen Ahmed
Northern Technical University
Computer Science & IT Electrical & Electronics Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Enhancing performance for three-phase induction motor by changing the magnetic flux density and core material using COMSOL Firas Saaduldeen Ahmed; Zozan Saadallah Hussain; Truska Khalid Mohammed Salih
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 1: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i1.pp62-72

Abstract

This paper presents a proposed design and analysis of a three-phase squirrel cage induction motor when changing of internal characteristic design for the three-phase induction motor. Two situations have been applied to enhancing the performance of the three-phase induction motor. The first situation has been implemented by changing the magnetic flux density (MFD) via the build of the six-phase for the same induction motor. The second situation has been implemented by changing core materials of the rotor part of the induction motor, like aluminum (AL) and cast iron (CI). The finite element method (FEM) has been used to analyze the rotor part, also to obtain the representation and simulation of the realty cylindrical rotor part of motor. The frequency domain (FD) analysis using to obtain the results within the environment of the COMSOL multiphysics 5.5 version.
Control of prosthetic hand by using mechanomyography signals based on support-vector machine classifier Firas Saaduldeen Ahmed; Noha Abed-Al-Bary Al-jawady
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 2: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i2.pp1180-1187

Abstract

Prosthetic devices are necessary to help amputees achieve their daily activity in the natural way possible. The prosthetic hand has controlled by type of signals such as electromyography (EMG) and mechanomyography (MMG). The MMG signals have represented mechanical signals that generate during muscle contraction. These signals can be detected by accelerometers or microphones and any kind of sensors that can detect muscle vibrations. The contribution of the current paper is classifying hand gestures and control prosthetic hands depends on pattern recognition through accelerometer and microphone are to detect MMG signals. In addition to the cost of prosthetic hand less than other designs. Six subjects are involved. In this present work is the devices. In this study, two of them are amputee subjects. Each subject performs seven classes of movements. Pattern recognition (PR) is used to classify hand gestures. The wavelet packet transform (WPT) and root mean square (RMS) as features extracted from the signals and support vector machine (SVM) as a classifier. The average accuracy is 88.94% for offline tests and 84.45% for online tests. 3D printing technology is used in this study to build prosthetic hands.
Co-Authors Noha Abed-Al-Bary Al-jawady Truska Khalid Mohammed Salih Zozan Saadallah Hussain