Yazar "Cekli, Serap" seçeneğine göre listele

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    Amplitude and Frequency Estimation of Power System Signals Using Independent Component Analysis
    (IEEE, 2013) Uzunoglu, Cengiz Polat; Ugur, Mukden; Turan, Faruk; Cekli, Serap
    In this paper independent component analysis (ICA) method for amplitude and frequency estimation of distorted power system signals is proposed. In order to protect system and keep it in safe operation mode the amplitude and frequency estimation should be conducted accurately. Transient disturbances of the power system may reduce estimation performance due to the distortion strength. In this study white noise and pulse noise which are very common for power systems, are used to contaminate power system signal. Thus, the proposed method is employed to decompose noise from system signal and hence to improve the efficiency of the estimation. Computer simulations have been carried out for the performance analysis of the ICA method and the comparison of the results of the proposed method with the conventional filters are displayed by using mean square error (MSE) values.
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    Compression of Medical Images With HEVC Intra Prediction Coding
    (IEEE, 2017) Akman, Ali; Cekli, Serap
    HEVC which is the new image coding standard provides higher compression performance over the existing standards. In this study, compression of medical images is fulfilled with HEVC intra prediction method. The compressed images for storage or transmission purposes should not lose their required characteristics for the diagnosis after the recovery process. The recovered compressed images are evaluated by using the objective criteria of PSNR values. The experimental results are provided in the study.
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    A Computationally Efficient Pipelined Architecture for 1D/2D Lifting Based Forward and Inverse Discrete Wavelet Transform for CDF 5/3 Filter
    (UNIV SUCEAVA, FAC ELECTRICAL ENG, 2018) Cekli, Serap
    In this study, a simple lifting based pipeline DWT (Discrete Wavelet Transform) architecture is proposed for the operation of the CDF 5/3 (Cohen-Daubechies-Feauveau 5/3) filter. This scalable architecture is faster and capable of fulfilling the transformation utilizing the parallel processing operation units. The symmetric boundary extension method is used at the signal boundaries to obtain the best result in the case of 1D/2D. The proposed architecture utilizes the hardware resources in a quite efficient way by means of the pipeline technique. The architectural design is constituted by using RTL (Register Transfer Level) design process and coded by the Verilog HDL. The proposed architecture is tested for several 1D/2D inputs to examine its operation. The related architecture is synthesized for the FPGA board to check the results. The reverse operation is fulfilled by using the same structure only by changing the shift amounts of the shifting units. The DWT coefficients are calculated on this architecture for the 1D/2D situation. The hardware resources are used effectively by utilizing the constituted architecture in folded structure in the 2D case. Satisfying results have been obtained when the different numbers of parallel processing units are utilized.
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    Design of Approximate Discrete Cosine Transform Architecture for Image Compression with HEVC Intra Prediction
    (Ieee, 2020) Akman, Ali; Cekli, Serap
    Discrete cosine transform (DCT) is an integral part of many image compression standards. Image compression with HEVC inra prediction method also uses DCT. Because the complexity of DCT is high, the complexity of the encoder hardware is high and the energy consumption of the encoder is also high. In this study, a new approximated DCT architecture is proposed to reduce the complexity and energy consumption of DCT hardware used in image compression by high efficiency video coding (HEVC) intra prediction method. This architecture is based on the use of shy and add operation instead of multiplication, and the use of approximate 5:3 compressor chains for addition operations..
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    An Efficient SPIHT Algorithm and System Architecture for Image Compression
    (IEEE, 2017) Cekli, Serap; Akman, Ali
    In this study, an efficient modified SPIHT algorithm and related architecture design is proposed for image compression. The proposed architecture is designed as a three stage pipeline structure. Different sized images are compressed using the designed architecture for different bpp values. The computed PSNR values of the compressed images using the proposed algorithm and also the original algorithm is compared in order to test the performance of the proposed algorithm and architecture.
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    An Improved Method for Lossless Compression of Volumetric Medical Images
    (Ieee, 2019) Akman, Ali; Cekli, Serap
    Size of volumetric medical images is very large. Because of this, some problems occur while storing or transmitting this type of data. So, it is necessary to compress volumetric medical images using efficient techniques. It is more appropriate to compress medical images using lossless techniques due to it may have effects on diagnosis. In this study, a method for lossless compression of volumetric medical images was proposed. The redundancy has been reduced using DPCM technique by utilizing correlation between image slices. SAP technique has been applied to first slice. The performance is improved by applying RDPCM for each image frame after DPCM, individiually. To investigate the performance of the proposed method, some experiments have been performed using different medical images and the results are presented.
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    KINECT BRAIN WAVES WITH CONTROLLED SMART AUTOMATION SYSTEM FOR ALS PATIENTS
    (IEEE, 2015) Kantekin, Ugur; Aytekin, Ugur; Alaybeyoglu, Busra; Cekli, Serap
    Nowadays, smart automation systems which directly affect people's life styles are being studied and designed frequently. These studies are carried out in a home environment, hospital or wheelchair to satisfy user's needs effectively. But these studies mainly focused on the healthy people. In this study a smart home automation system is proposed for ALS patients, orthopedic disabilities. In this work, Emotive device, Kinect One and Arduino Yin microcontroller were used to establish automation system which will render especially disabled people's daily life more safely and practically while they are at home.
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    LOCATION ESTIMATION OF BROADBAND SOURCE WITH ADAPTED MUSIC ALGORITHM
    (Istanbul Univ, Fac Engineering, 2010) Cekli, Serap
    This study deals with location estimation of the broadband acoustic source in the distributed sensor network. The proposed algorithm is based on the MUSIC (Multiple Signal Classification) algorithm, which solves the localization problem in time domain. The broadband source signal arrives at each sensor with different amplitudes and delay times. Therefore, the signals which are reached at the sensors are the noisy versions of the each other. The collected sensor data is called the observation set, and the cross correlation matrix is calculated by using the observation set. The correlation matrix provides a measure of the similarity between each sensor signal and the relative delay time between the received sensor signals which can be determined by using this data. A reference time point is chosen among the received signals and each time delays are eliminated according to this signal after calculating the cross correlation matrix. Consequently, the source location estimation task is performed by MUSIC algorithm in time domain. Moreover, the simulation results which demonstrate the performance of the method are given in the paper.
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    Location estimation of partial discharge-based electromagnetic source using multilateration with time difference of arrival method
    (SPRINGER, 2018) Gulnihar, Kaan; Cekli, Serap; Uzunoglu, Cengiz Polat; Ugur, Mukden
    In high-voltage systems partial discharges (PD) may occur due to the degradation of insulation materials in addition to different scenarios such as material properties, construction, setup and operation conditions. Especially for a power transformer, the degradation of inner insulation may prevent regular operation and hence cause failure. In a long time period even low-level PD activity may cause degradation on the insulator. If the deterioration caused by the PD is detected in an early phase, potential damage may be prevented. Due to the complex and close structure of power transformers and other high-voltage systems, it is not easy to estimate the exact location of a PD. This study proposes a novel approach to detect and analyze an artificial PD in a laboratory room setup, which is especially designed for simulation of possible PD source in a large scale structure such as power transformer. Electromagnetic (EM) PD sensors are commonly used to detect electromagnetic pulses emitted from PD sources. In this work, the time differences of arrivals (TDOA) which are obtained from PD signals are subjected to multilateration technique to estimate the exact location. A novel energy level method is introduced to overcome correct TDOA extraction problem. Cramer-Rao bound (CRB) is used for calculation of the minimum achievable estimation error of proposed method. In order to display the accuracy of location estimation, CRB and the mean square error graphics of the estimated location parameters are given for the comparison.
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    MODELLING OF CHAOTIC SURFACE TRACKING ON THE POLYMERIC INSULATORS WITH HIDDEN MARKOV MODELS
    (IEEE, 2014) Uzunoglu, Cengiz Polat; Cekli, Serap; Ugur, Mukden
    In this study, chaotic surface tracking patterns observed on polymeric high voltage (HV) outdoor insulation materials were investigated and simulated The polymeric samples are tested according to the IEC 587 Inclined Plane Tracking Test Standard Since the chaotic surface tracking patterns manifests smutty and disordered images, they are preprocessed and purified by image processing tools. Internal and external effects may severely decrease insulation performance. In order to examine external effects, samples are subjected to moisture and vibration effect Polymer samples are investigated by their fractal dimension which is a prominent tool for analyzing chaotic images. To simulate these chaotic surface tracking patterns Hidden Markov Models (HMM) are used
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    Monofractal and Multifractal Analysis of Discharge Signals in Transformer Pressboards
    (UNIV SUCEAVA, FAC ELECTRICAL ENG, 2018) Cekli, Serap; Uzunoglu, Cengiz Polat; Ugur, Mukden
    Pressboards are commonly used as insulating materials employed in electrical connections of transformers. Pressboards are typically made from vegetable fibers, which contain cellulose. The proper operation of power transformer depends mainly on constant monitoring of insulation materials against failure. Due to the complex and close structure of power transformers, it is very challenging task to detect failure and hence possible location of degradation of pressboard internally. Generated discharge signals may result in breakdown of system insulation and system failure. In this study, the investigation of insulation degradation is fulfilled by analyzing discharge signals and simultaneously produced acoustic signals during discharges. For this purpose, a test setup is used for investigating discharge signals of pressboard samples under different electrical stresses. This paper proposes monofractal and multifractal analysis of discharge and acoustic signals of pressboards. The Higuchi's method is an effective monofractal analysis tool for measurement of fractal dimension of self-affine signals, which is proposed for online monitoring of discharge signals of pressboards. In order to investigate obtained discharge signals with accelerated fluctuations effectively, multifractal detrended fluctuation analysis is proposed for these signals, which exhibit nonlinear behavior.
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    Power-Efficient Viterbi Decoder Architecture and Field Programmeble Gate Arrays Fpga Implementation
    (ISTANBUL UNIV, FAC ENGINEERING, 2018) Ozbay, Burcu; Cekli, Serap
    A Viterbi decoder system comprises a convolutional encoder and Viterbi decoder. In general, the code words generated from the input series of convolutional encoder arrive at the decoder through a noisy channel; however, the channel noise can cause corruption of code words. The Viterbi decoder extracts the original input message from the corrupted data using the Viterbi algorithm based on the maximum likelihood principle. A Viterbi decoder mainly comprises four essential units: a branch metrics unit, add-compare-select unit, path metrics unit, and survivor-path memory unit. Related complex calculations are repeated in these units at each clock cycle. In this study, a power- and area-efficient Viterbi decoder architecture that also reduces the computational complexity is proposed. Initially, a hard-decision Viterbi decoder system architecture design for Very Large Scale Integration (VLSI) realization was fulfilled without any further improvement to compare the performance of fundamental and improved designs with respect to power consumption. The initial design constitutes an essential base for the improved power- and area-efficient Viterbi decoder architecture. The improvements were made to achieve the less complex and power-efficient architectural system design. The performance of the proposed architecture was tested by a fieldprogrammable gate array (FPGA) platform, and the results have been reported. The architectural design is described using the Verilog hardware description language for comparing the related tests and performance of FPGA platform.
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    Statistical analysis of induced magnetic fields on oil-impregnated insulation pressboards
    (SPRINGER, 2020) Atalar, Fatih; Uzunoglu, Cengiz Polat; Cekli, Serap; Ugur, Mukden
    Electrical insulation materials are highly exposed to electrical network-based electric and magnetic fields in power systems. In electrical fields, electrical insulation materials are prone to breakdown and cause failure. A transformer failure which is related to pressboard insulation may lead to total breakdown and hence system malfunction in a total manner. In this study, a test setup is used to conduct discharge tests for pressboards in different thicknesses where main interest is originated magnetic fields on the pressboards. These tests are fulfilled with spherical and rod electrodes in transformer oil where magnetic field sensors are used to acquire discharge-based magnetic field data. By investigating high-voltage stresses with different levels, possible breakdown voltage of a pressboard is predicted and statistically analyzed. In addition to magnetic field measurements, discharge current measurements are taken; however, contrary to conventional studies, this study assesses magnetic field data which are dependent on the thickness of pressboard insulation. For different voltage levels (13 kV and 22 kV for different stress levels), magnetic field measurements and current waveforms are obtained by using magnetic field sensors and high-speed oscilloscope. Magnetic field time series signals are subjected to wavelet analysis, and wavelet coefficients are obtained. Rather than utilizing time series current signals or time series magnetic field signals, wavelet coefficients of magnetic field signals are taken into consideration as a novel approach. These coefficients are processed by multifractal analysis, and finally, the integrity of the pressboard is determined as in proper mode (no failure) or in breakdown mode.