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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 9,174 Documents
 34   35   36   37   38 
Peak Power Reduction Using Improved Selective Mapping Technique for OFDM Muhmmad Rizwan Anjum; Mussa A. Dida; M. A. Shaheen
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 8: August 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i8.pp6291-6296

Abstract

OFDM has Major disadvantage is that  it leads to high Peak to Average Power Ratio (PAPR) which is consider to be as the main implementation drawback.  In this paper we are discussing about PAPR which affects the performance and efficiency of Power Amplifier (PA) and its influence by utilizing the Selective Mapping (SLM) technique in OFDM system for reduction of PAPR. the idea for improved SLM produces several independent signals based on converting the original data lock into many independent signal and then the signal has lowest PAPR that specific signal is  transmitted. Also data rate trade-off exist at the receiver end  when side information is detected for the  recovery of data block. which leads to the reduction of data rate. Improved SLM techniques for reducing the PAPR is the most promising reduction technique in its non-uniform phase factor for PAPR reduction in multicarrier OFDM system. Furthermore the estimate  expression by using Complementary Cumulative Distribution Function (CCDF) for PAPR has been discussed. Simulated results demonstrate that OFDMA signals using improved SLM technique carried significant effects in reduction of PAPR in OFDM system.
Study on BSS Algorithm used on Fault Diagnosis of Gearbox Yu Chen; Jintao Meng
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 6: June 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

The gearbox is a complicated rotating machinery equipment, in order to realize the gearbox fault early detection and prevention, it is the key to carry out the online diagnosis. This paper used the adaptive variable step-length natural gradient blind source separation algorithm to realize the helicopter gearbox meshing vibration signal and fault vibration signal effective separation. Through the algorithm simulation, the accuracy of the algorithm gained the verification and the separation error trended to zero, which has higher separation precision. This algorithm can realize the complicated mechanical vibration signal blind source separation and fault diagnosis, which has a broad application prospect. DOI: http://dx.doi.org/10.11591/telkomnika.v11i6.2260
Analysis of Impact Fatigue Life for Valve Leaves in Small Hermetic Reciprocating Compressors Dong Zhang; Ming Xu; Jiang-Ping Gu; Yue-Jin Huang; Xi Shen
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 12: December 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

Impact fatigue life of valve leaves has great influence on energy saving performance and lifetime of small hermetic reciprocating compressors. This paper presented a test system that intended to analysis and evaluate of impact fatigue life of valve leaves used in small hermetic reciprocating compressors. Firstly, an incentive system was designed to simulate real work condition for valve leaf. Then, a data acquisition system was built to collect the sound signal while valve leaf was being under test. Simultaneously, the system could control the working state of incentive system so that test could be terminated automatically once fatigue was detected. Finally, fatigue detection system was designed to detect fatigue of valve leaf. Fatigue detection was the key point of this test system. Fast Fourier Transform (FFT) and Wavelet Packet Transform (WPT) were applied to analyze sound signal, both of which were effective in detecting the damage through analyzing. Facts showed that the test system provided a feasible approach to evaluate impact fatigue life for valve leaf manufacturing. DOI: http://dx.doi.org/10.11591/telkomnika.v11i12.3675
Edge detection Using Histogram Localization Mohamed Asharudeen; Hema P Menon
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 1: July 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i1.pp341-355

Abstract

Detection of edges under noisy environments has been gaining lot of prominence in the recent past in most of the image and video processing applications. In this work a novel approach based on the distribution of intensity values and their corresponding positions has been proposed for distinguishing the edge pixels from the grey scale images. Separate histogram has been maintained for X and Y coordinates. The first order derivative is applied over these histograms to distinguish the edge pixels. The pixel with gradient distribution below a specific threshold value is selected as an edge pixel. This method is found to work well in case of both noiseless and noisy images. Hence this method is able to perceive the underlying information in case of noisy images also. The proposed algorithm can be used for both low and high resolution images. However, the performance of the algorithm is more evident in high resolution image. A general analysis of the proposed method has been conducted for arbitrary images. The major application of the proposed work can be used for the applications that doesn’t need any preprocessing or to avoid any loss of information like in medical image analysis as it contemplate towards every intensity bin to trace the edges present in the histogram of the image rather than the overall image concerning for direct edge tracing. The results have been compared with canny algorithm which is most commonly used for edge detection.
Web Based Automated Smart House Management Navya Navya; Ganesh Dumala
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 3: March 2015
Publisher : Institute of Advanced Engineering and Science

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Abstract

A Home automation refers to control appliances around the home. These appliances can include lights, fans and other electronic devices. Instead of using GSM and ZIGBEE modules use a simple system to reduce complexity. Here the proposed system uses web server using microcontroller. The proposed system gives users an effective and easy way of controlling the various home appliances from a remote location i.e. without physically being present at home. This system can control the fans and lights. Microcontroller is used to acquire data from different types of sensors. It can monitor the appliances from anywhere with the help of web page. DOI: http://dx.doi.org/10.11591/telkomnika.v13i3.7173 
Stator winding fault detection of induction generator based wind turbine using ANN N. F. Fadzail; S. Mat Zali; M. A. Khairudin; N. H. Hanafi
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 1: July 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i1.pp126-133

Abstract

This paper presents a stator winding faults detection in induction generator based wind turbines by using artificial neural network (ANN). Stator winding faults of induction generators are the most common fault found in wind turbines. This fault may lead to wind turbine failure. Therefore, fault detection in induction generator based wind turbines is vital to increase the reliability of wind turbines. In this project, the mathematical model of induction generator based wind turbine was developed in MATLAB Simulink. The value of impedance in the induction generators was changed to simulate the inter-turn short circuit and open circuit faults. The simulated responses of the induction generators were used as inputs in the ANN model for fault detection procedures. A set of data was taken under different conditions, i.e. normal condition, inter-turn short circuit and open circuit faults as inputs for the ANN model. The target outputs of the ANN model were set as ‘0’ or ‘1’, based on the fault conditions. Results obtained showed that the ANN model can detect different types of faults based on the output values of the ANN model. In conclusion, the stator winding faults detection procedure for induction generator based wind turbines by using ANN was successfully developed.
Algorithms for Lorenz System Manifold Computation Meng Jia; Bing Wu
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 4: April 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

A new algorithm is presented to compute both one dimensional stable and unstable manifolds of planar maps. It is proved that the gradient of the global manifold can be predicted by the known points on the manifold with a gradient prediction scheme and it can be used to locate the image or preimage of the new point quickly. The performance of the algorithm is demonstrated with hyper chaotic Lorenz system. DOI : http://dx.doi.org/10.11591/telkomnika.v12i4.4740
Wireless Sensor Networks Node Localization-A Performance Comparison of Shuffled Frog Leaping and Firefly Algorithm in LabVIEW Chandirasekaran D; T. Jayabarathi
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 3: June 2015
Publisher : Institute of Advanced Engineering and Science

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Abstract

Wireless sensor networks (WSN) have become popular in many applications area including environmental monitoring, military and offshore oil & gas industries. In WSN the sensors are randomly deployed in the sensor field and hence estimation of the localization of each deployed node has drawn more attention by the recent researchers, It’s a unique problem to identify and maximizing the coverage where the sensors need to be placed in a position so that the sensing capability of the network is fully utilized to ensure high quality of service. In order to keep the cost of sensor networks to a minimum, the use of additional hardware like global positioning system (GPS) can be avoided by the use of effective algorithms that can be used for the same. In this paper we attempted to use both the shuffled frog leaping (SFLA) and firefly algorithms (FFA) to estimate the optimal location of randomly deployed sensors. The results were compared and published for the usefulness of further research. DOI: http://dx.doi.org/10.11591/telkomnika.v14i3.7861
Metropolis Criterion Based Fuzzy Q-Learning Energy Management for Smart Grids Xin Li; Chuanzhi Zang; Wenwei Liu; Peng Zeng; Haibin Yu
Indonesian Journal of Electrical Engineering and Computer Science Vol 10, No 8: December 2012
Publisher : Institute of Advanced Engineering and Science

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Abstract

For the energy management problems for demand response in electricity grid, a Metropolis Criterion based fuzzy Q-learning consumer energy management controller (CEMC) is proposed. Because of the uncertainties and highly time-varying, it is not easy to accurately obtain the complete information for the consumer behavior in electricity grid. In this case, the Q-learning, which is independent of mathematic model, and prior-knowledge, has good performance. The fuzzy inference and Metropolis Criterion are introduced in order to facilitate generalization in large state space and balance exploration and exploitation in action selection in Q-learning individually. Simulation results show that the proposed controller can learn to take the best action to regulate consumer behavior with the features of low average end-user financial costs and high consumer satisfaction. DOI: http://dx.doi.org/10.11591/telkomnika.v10i8.1626
A Clustering Algorithm Based on Rough Set and Genetic Algorithm Yushu Xiong
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 10: October 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

With the development of computer and information technology, the capacity of data and information is increasing. The processing of data and information becomes the hot issue in the current scientific community. Rough set and genetic algorithm are two data mining and processing technologies which had been commonly used. Rough set can process data quickly and the algorithm is simple. The convergence of genetic algorithm is fast and the robustness is good. This paper puts forward the effective clustering algorithm based on  the combined control of rough set and genetic algorithm, then does simulation experiment of segmentation images by  numerical simulation based on matlab programming, finally gets  the curve of calculation process and the effect diagram of image segmentation , verifies the effectiveness of the algorithm. DOI: http://dx.doi.org/10.11591/telkomnika.v11i10.3407

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