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Status Review on Gas Insulated Switchgear Partial Discharge Diagnostic Technique for Preventive Maintenance
Visa Musa Ibrahim;
Zulkurnain Abdul-Malek;
Nor Asiah Muhamad
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v7.i1.pp9-17
Gas insulated switchgear (GIS) plays a vital role in high voltage transmission of electrical energy due to its advantages of high reliability and performance, compact in dimensions and outstanding compatibility with the environment. It uses sulphur hexafluoride gas as its insulant and coolant because of its high dielectric strength and excellent arc quenching ability. Gas insulated switchgear in operation suffers the challenge of its insulation decomposition and eventually failure due to the activities of partial discharge that arouses from defects. This failure is catastrophic and it will lead to entire power out stage that will affect all categories of human activities, so there is a need for Gas insulated switchgear condition monitoring and diagnoses in order to carry out preventive maintenance. This paper reviews diagnostic techniques and methods for Gas insulated switchgear insulation degradation caused by partial discharge for the purpose of carrying out preventive maintenance to avert its failure.
MRI Denoising using Sparse Based Curvelet Transform with Variance Stabilizing Transformation Framework
Sidheswar Routray;
Arun Kumar Ray;
Chandrabhanu Mishra
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v7.i1.pp116-122
We develop an efficient MRI denoising algorithm based on sparse representation and curvelet transform with variance stabilizing transformation framework. By using sparse representation, a MR image is decomposed into a sparsest coefficients matrix with more no of zeros. Curvelet transform is directional in nature and it preserves the important edge and texture details of MR images. In order to get sparsity and texture preservation, we post process the denoising result of sparse based method through curvelet transform. To use our proposed sparse based curvelet transform denoising method to remove rician noise in MR images, we use forward and inverse variance-stabilizing transformations. Experimental results reveal the efficacy of our approach to rician noise removal while well preserving the image details. Our proposed method shows improved performance over the existing denoising methods in terms of PSNR and SSIM for T1, T2 weighted MR images.
Design of Remote Control Juvenile Healthy Smart Pillow
Huadong Zhou;
Xuran He;
Jiaheng Yang;
Lifan Liao
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v7.i1.pp97-106
High-quality modern life results in many unique diseases of modern people, cervical spondylosis, sleep disorders. Adolescents lack of sleep have a negative impac on the students themselvest. Not only it will reduce the body resistance, prone to a variety of diseases, but also it make learning when the spirit is not concentrated, attention is decreased, thus affecting the learning state. Long-term lack of sleep will lead to psychological problems, a potential threat is formed to the physical and mental health of young people. To this end, based on WeChat platform, a young people's health intelligence pillow is designed, it can be remotely controned.
The Maximal SINR Selection Mode for 5G Millimeter-Wave MIMO: Model Systems and Analysis
Dinh-Thuan Do;
Duc-Anh Nguyen
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v7.i1.pp150-157
In mmWave massive MIMO systems, the lens antenna array and beam selection by beamspace MIMO are employed to target the number of required RF chains reduced without obvious performance loss. For cost – effective, the number of RF chain is an allowable limitation, however, to obtain the near-optimal capacity efficiently, beam selection must require the exact information of the wide size of beamspace channel. Solution to this problem, in this paper we suggest analyzing whole beamspace based on maximal SINR. More specicfically, it is confirmed that the proposed beam selection algorithms achieve higher power efficiencies than a full system where all beams are employed.
Prototype Design of Smart Home System using Internet of Things
Teddy Surya Gunawan;
Intan Rahmithul Husna Yaldi;
Mira Kartiwi;
Nanang Ismail;
Nor Farahidah Za'bah;
Hasmah Mansor;
Anis Nurashikin Nordin
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v7.i1.pp107-115
Smart home control system can be integrated into an existing home appliances to reduce the need for human intervention, increase security and energy efficiency. However, it is still an open problem due to difficulties such as network distance, signal interference, not user friendly, increased cost and power consumption. This paper reviews various topics on smart home technologies including control system, smart home network, smart home appliance and sensor technologies for smart home. In this research, the proposed prototype of home automation allows users to remotely switch on or off any household appliance based on Internet of Things (IoT) with the enhancement of solar charger. The smartphone and/or tablet replaces the manual use of personal computer without the need for high additional cost. This prototype uses four types of sensors i.e. PIR sensor, temperature sensor, ultrasonic sensor and smoke gas sensor for automatic environmental control and intrusion detection.
Design and Simulation of a New ZVT Bi-directional DC-DC Converter for Electric Vehicles
Rajesh Thumma;
Veera Venkata Subrahmanya Kumar Bhajana;
Pramo kumar Aylapogu
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v7.i1.pp75-83
This paper presents a new zero voltage transistion (ZVT) bi-directional DC-DCconverter for energy storage system in DC traction. This bidirectional converter can transfers the power flow from low voltage side to high voltage side and viceversa. The conventional hard-switched non-isolated converter improved with the additional auxiliary cell to obtain zero voltage transition for the IGBTs. The main advantages of this topology are reduced the switching losses and improved the efficiency as well.The main aim of this converter is to achieve the operation of zero voltage transition during the commutation of main switches from off to on by utilizing auxiliary cell, which consist active and passive elements.The boost and buck modes of operations are achieved with the zero voltage transistion, which reduce the IGBTs current stresses and switching losses.This paper mainly describes the operation principles and the evaluation of the simulation results with the aid of Matlab simulations.The obtained results were proved the expected assumptions of the theoretical analysis.
Multiple DG Planning Considering Distribution Loss and Penetration Level using EMEFA-ANN Method
S. R. A. Rahim;
I. Musirin;
M. M. Othman;
M. H. Hussain
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v7.i1.pp1-8
This paper presents the implementation of multiple distributed generation planning in distribution system using computational intelligence technique. A pre-developed computational intelligence optimization technique named as Embedded Meta EP-Firefly Algorithm (EMEFA) was utilized to determine distribution loss and penetration level for the purpose of distributed generation (DG) installation. In this study, the Artificial Neural Network (ANN) was used in order to solve the complexity of the multiple DG concept. EMEFA-ANN was developed to optimize the weight of the ANN to minimize the mean squared error. The proposed method was validated on IEEE 69 Bus distribution system with several load variations scenario. The case study was conducted based on the multiple unit of DG in distribution system by considering the DGs are modeled as type I which is capable of injecting real power. Results obtained from the study could be utilized by the utility and energy commission for loss reduction scheme in distribution system.
Comparative Study of Fuzzy Logic Mobility Based FLM-AODV Routing Protocol and AODV in MANETs
Vivek Sharma;
Bashir Alam;
M. N. Doja
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v7.i1.pp158-163
In mobile ad hoc wireless networks (MANETs), traditional protocol like AODV performs well for low mobility of nodes but not for high node mobility. So, it becomes important to consider mobility factor during the path selection procedure of routing protocol. Here, a fuzzy logic mobility based protocol (FLM-AODV) that considers the mobility factor is proposed. Due to the consideration of mobility factor, the proposed protocol has better performance than the traditional AODV. The experiment results show that the proposed protocol has advantages of improved average end-to-end delay and packet delivery ratio (PDR) over existing AODV protocol.
A New Method of Voltage Flicker Detection for Hilbert Vibration Decomposition
Tiejun Cao
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v7.i1.pp43-51
Hilbert Vibration Decomposition (HVD) is introduced to the voltage flicker analysis. When voltage flicker accompanies with high order harmonics, the instantaneous frequency of its analytic signal in principle consists of two different parts, power frequency and a rapidly varying asymmetrical oscillating part. The important property of the instantaneous frequency offers a direct way to estimate the power frequency using a low-pass filter and remove the high order harmonics without pre-treatment procedures. Corresponding voltage flicker envelope is estimated using synchronous detection. The HVD method does not involves basic functions that the wavelet transform method needs. It can also adaptively estimate the frequency and amplitude of every modulation frequency component. Simulation results prove that the proposed method could accurately detect voltage flicker with high order harmonics. It has higher calculation efficiency and detection precision than wavelet transform method. Experimental results show that the new algorithm is feasible and efficient.
A Hybrid Feature Selection Based on Mutual Information and Genetic Algorithm
Yuan-Dong Lan
Indonesian Journal of Electrical Engineering and Computer Science Vol 7, No 1: July 2017
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v7.i1.pp214-225
Feature selection aims to choose an optimal subset of features that are necessary and sufficient to improve the generalization performance and the running efficiency of the learning algorithm. To get the optimal subset in the feature selection process, a hybrid feature selection based on mutual information and genetic algorithm is proposed in this paper. In order to make full use of the advantages of filter and wrapper model, the algorithm is divided into two phases: the filter phase and the wrapper phase. In the filter phase, this algorithm first uses the mutual information to sort the feature, and provides the heuristic information for the subsequent genetic algorithm, to accelerate the search process of the genetic algorithm. In the wrapper phase, using the genetic algorithm as the search strategy, considering the performance of the classifier and dimension of subset as an evaluation criterion, search the best subset of features. Experimental results on benchmark datasets show that the proposed algorithm has higher classification accuracy and smaller feature dimension, and its running time is less than the time of using genetic algorithm.