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INDONESIA
Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Published by IAES Indonesia Section and Partners
ISSN : 20893272     EISSN : -     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is a peer reviewed International Journal in English published four issues per year (March, June, September and December). The aim of Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is to publish high-quality articles dedicated to all aspects of the latest outstanding developments in the field of electrical engineering. Its scope encompasses the engineering of Telecommunication and Information Technology, Applied Computing & Computer, Instrumentation & Control, Electrical (Power), Electronics, and Informatics.
Arjuna Subject : -
Articles 24 Documents
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Search results for , issue "Vol 8, No 2: June 2020" : 24 Documents clear
Impact of unbalanced harmonic loads towards winding temperature rise using FEM modeling D.M. Said; Z.I.M. Yassin; N. Ahmad; NN Nik Abd Malik; H. Abdullah
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 2: June 2020
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (747.963 KB) | DOI: 10.52549/ijeei.v8i2.1283

Abstract

This paper investigates the hot spot temperature of transformer thermal model due to unbalanced harmonic loads from the network. The finite element method has been used to solve the coupling multiphysic for heat transfer in solid and fluid. All material properties in the model were been took into consideration such as copper as the coil material, iron as the core material and transformer oil as the coolant material for the transformer. The transient study on the model has been set for 1minutes using 30 degree celcius as the ambient temperature reference. The simulation hot spot temperature result has been compared for rated load (without harmonic) versus the unbalanced load (with harmonic) which shown in 2D regime. It can be clearly seen the significant increment of the hotspot temperature of the transformer from the rated load to the unbalanced harmonic load. The result has successfully shows the detection of the prospect failure of the transformer due to the harmonic current load in a form of winding loss that contributes to the hotspot temperature of the transformer.
Impact of unbalanced harmonic loads towards winding temperature rise using FEM modeling Said, D.M.; Yassin, Z.I.M.; Ahmad, N.; Malik, NN Nik Abd; Abdullah, H.
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 2: June 2020
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (747.963 KB) | DOI: 10.52549/ijeei.v8i2.1283

Abstract

This paper investigates the hot spot temperature of transformer thermal model due to unbalanced harmonic loads from the network. The finite element method has been used to solve the coupling multiphysic for heat transfer in solid and fluid. All material properties in the model were been took into consideration such as copper as the coil material, iron as the core material and transformer oil as the coolant material for the transformer. The transient study on the model has been set for 1minutes using 30 degree celcius as the ambient temperature reference. The simulation hot spot temperature result has been compared for rated load (without harmonic) versus the unbalanced load (with harmonic) which shown in 2D regime. It can be clearly seen the significant increment of the hotspot temperature of the transformer from the rated load to the unbalanced harmonic load. The result has successfully shows the detection of the prospect failure of the transformer due to the harmonic current load in a form of winding loss that contributes to the hotspot temperature of the transformer.
The Segmentation Analysis of Retinal Image Based on K-means Algorithm for Computer-Aided Diagnosis of Hypertensive Retinopathy Wiharto Wiharto; Esti Suryani
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 2: June 2020
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (605.838 KB) | DOI: 10.52549/ijeei.v8i2.1287

Abstract

Computer-aided diagnosis of hypertensive retinopathy (CAD-HR) is performed by analyzing the retinal image. The analysis is carried out in several stages, one of which is image segmentation. The segmentation carried out so far generally uses a region-based and threshold-based approach. There is not yet a clustering-based approach, and there has been no previous analysis of why clustering-based is not yet widely used. This study aims to conduct clustering-based Segmentation analysis, specifically k-means clustering in CAD-HR. The research method used is divided into four stages, namely preprocessing, segmentation, feature extraction using fractal dimensions, statistical analysis for classification, and classification. Testing is done using the DRIVE and STARE datasets. The results of statistical tests showed that the number of clusters 3 was able to provide a significant difference between the fractal positive and negative dimensions of hypertensive retinopathy. The model of CAD-RH using the k-means algorithm for segmentation method is able to provide 80% sensitivity performance. The k-mean algorithm can be used as an alternative to segmenting retinal blood vessels.
The Segmentation Analysis of Retinal Image Based on K-means Algorithm for Computer-Aided Diagnosis of Hypertensive Retinopathy Wiharto, Wiharto; Suryani, Esti
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 8, No 2: June 2020
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (605.838 KB) | DOI: 10.52549/ijeei.v8i2.1287

Abstract

Computer-aided diagnosis of hypertensive retinopathy (CAD-HR) is performed by analyzing the retinal image. The analysis is carried out in several stages, one of which is image segmentation. The segmentation carried out so far generally uses a region-based and threshold-based approach. There is not yet a clustering-based approach, and there has been no previous analysis of why clustering-based is not yet widely used. This study aims to conduct clustering-based Segmentation analysis, specifically k-means clustering in CAD-HR. The research method used is divided into four stages, namely preprocessing, segmentation, feature extraction using fractal dimensions, statistical analysis for classification, and classification. Testing is done using the DRIVE and STARE datasets. The results of statistical tests showed that the number of clusters 3 was able to provide a significant difference between the fractal positive and negative dimensions of hypertensive retinopathy. The model of CAD-RH using the k-means algorithm for segmentation method is able to provide 80% sensitivity performance. The k-mean algorithm can be used as an alternative to segmenting retinal blood vessels.

Page 3 of 3 | Total Record : 24

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