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Full-Text Articles in Engineering
Partial Discharge Detection And Localization On The Medium Voltage Xlpe Cableswith Multiclass Support Vector Machines, Fati̇h Serttaş, Fati̇h Onur Hocaoğlu
Partial Discharge Detection And Localization On The Medium Voltage Xlpe Cableswith Multiclass Support Vector Machines, Fati̇h Serttaş, Fati̇h Onur Hocaoğlu
Turkish Journal of Electrical Engineering and Computer Sciences
In medium voltage cables, partial discharges (PD?s) are the major problems that trigger electrical insulation failures. Therefore, classification of PD source type and failure localization in medium voltage cables are significant issues of medium voltage engineering. Therefore, in this study, both detection and localization of PD are studied. As a first step, 4 different kind of defects are artificially generated at the same length of the same kind of medium voltage cross-linked polyethylene (XLPE) cables. Consequently, an experimental setup is built. During the experiments, different medium voltage levels are applied to the cables, then the PD signals are measured and …
Symptom-Aware Hybrid Fault Diagnosis Algorithm In The Network Virtualization Environment, Yuze Su, Xiangru Meng, Xiaoyang Han, Qiaoyan Kang
Symptom-Aware Hybrid Fault Diagnosis Algorithm In The Network Virtualization Environment, Yuze Su, Xiangru Meng, Xiaoyang Han, Qiaoyan Kang
Turkish Journal of Electrical Engineering and Computer Sciences
As an important technology in next-generation networks, network virtualization has received more and more attention. Fault diagnosis is the crucial element for fault management and it is the process of inferring the exact failure in the network virtualization environment (NVE) from the set of observed symptoms. Although various traditional fault diagnosis algorithms have been proposed, the virtual network has some new characteristics, which include inaccessible fault information of the substrate network, inaccurate network observations, and a dynamic embedding relationship. To solve these challenges, a symptom-aware hybrid fault diagnosis (SAHFD) algorithm in the NVE is proposed in this paper. First, a …
Automatic Fault Isolation And Restoration Of Distribution System Using Jade Based Multi-Agents, Indhumathi Chellaswamy, Joy Vasantha Rani Sp
Automatic Fault Isolation And Restoration Of Distribution System Using Jade Based Multi-Agents, Indhumathi Chellaswamy, Joy Vasantha Rani Sp
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a solution for automatic service restoration along with automatic fault location and isolation of the faulty sections in feeder in a power distribution system. A Java agent development environment-based multiagent system (MAS) is proposed to solve the problem of automatic service restoration in smart grid distribution systems. The agent-based solution development is discussed in detail and the MAS application to solve power restoration problem is elaborated in this paper. A study is done on a modified IEEE 33 bus system and the solution is implemented in the Velachery substation of the Tamilnadu electricity board. The results prove …
Transformer Incipient Fault Diagnosis On The Basis Of Energy-Weighted Dga Usingan Artificial Neural Network, Md Danish Equbal, Shakeb Ahmad Khan, Tarikul Islam
Transformer Incipient Fault Diagnosis On The Basis Of Energy-Weighted Dga Usingan Artificial Neural Network, Md Danish Equbal, Shakeb Ahmad Khan, Tarikul Islam
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a transformer incipient fault diagnosis model has been developed with the help of an artificial neural network (ANN), taking into account the difference in the energy required to produce the different fault gases. The key fault gases are indicative of the fault type prevailing in the transformer. However, in conventional studies, the energy difference in fault gas formation is not considered while adopting the key gas method for fault diagnosis. In this work, a weighting factor has been used to take into account this relative difference in energy requirement for various fault gas formations. The fault gas …
A Novel Perturbed Particle Swarm Optimization-Based Support Vector Machine Forfault Diagnosis In Power Distribution Systems, Hoang Thi Thom, Cho Ming-Yuan, Vu Quoc Tuan
A Novel Perturbed Particle Swarm Optimization-Based Support Vector Machine Forfault Diagnosis In Power Distribution Systems, Hoang Thi Thom, Cho Ming-Yuan, Vu Quoc Tuan
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a novel perturbed particle swarm optimization (PPSO) algorithm is investigated to improve the performance of a support vector machine (SVM) for short-circuit fault diagnosis in power distribution systems. In the proposed PPSO algorithm, the velocity of each particle is perturbed whenever the particles strike into a local optimum, in order to achieve a higher quality solution to optimization problems. Furthermore, the concept of proposed perturbation is applied to three variants of PSO, and improved corresponding algorithms are named perturbed C-PSO (PC-PSO), perturbed T-PSO (PT-PSO), and perturbed K-PSO (PK-PSO). For the purpose of fault diagnosis, the time- domain …
Eccentricity Fault Diagnosis In A Permanent Magnet Synchronous Motor Under Nonstationary Speed Conditions, Mustafa Eker, Mehmet Akar
Eccentricity Fault Diagnosis In A Permanent Magnet Synchronous Motor Under Nonstationary Speed Conditions, Mustafa Eker, Mehmet Akar
Turkish Journal of Electrical Engineering and Computer Sciences
Electric motor faults decrease production capacity and increase maintenance costs. Today, predictive detection based on real-time monitoring and fault detection is taking the place of periodic applications. In this study, a new method is presented for the detection of eccentricity faults in permanent magnet synchronous motors. The motor current and the rotor speed were monitored under stationary and nonstationary speed and different load conditions, after which the fault detection was carried out via angular domain-order tracking method. The obtained results were compared with traditional fast Fourier transform results. It was observed that the suggested method can successfully detect the fault …
A Robust Algorithm Based On A Failure-Sensitive Matrix For Fault Diagnosis Of Power Systems: An Application On Power Transformers, Yunus Bi̇çen, Faruk Aras
A Robust Algorithm Based On A Failure-Sensitive Matrix For Fault Diagnosis Of Power Systems: An Application On Power Transformers, Yunus Bi̇çen, Faruk Aras
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a robust algorithm for fault diagnosis of power system equipment based on a failure-sensitive matrix (FSM) is presented. The FSM is a dynamic matrix structure updated by multiple measurements (online) and test results (offline) on the systems. The algorithm uses many different artificial intelligence and expert system methods for adaptively detecting the location of faults, emerging failures, and causes of failures. In this algorithm, all data obtained from the power transformer, which have various nonlinear input and output parameters, are processed using the parallel matrix structure of the FSM to reach a global solution quickly. The parameters …
Artificial Immunity-Based Induction Motor Bearing Fault Diagnosis, Hakan Çaliş, Abdülkadi̇r Çakir, Emre Dandil
Artificial Immunity-Based Induction Motor Bearing Fault Diagnosis, Hakan Çaliş, Abdülkadi̇r Çakir, Emre Dandil
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, the artificial immunity of the negative selection algorithm is used for bearing fault detection. It is implemented in MATLAB-based graphical user interface software. The developed software uses amplitudes of the vibration signal in the time and frequency domains. Outer, inner, and ball defects in the bearings of the induction motor are detected by anomaly monitoring. The time instants of the fault occurrence and fault level are determined according to the number of activated detectors. Anomaly detection in the frequency domain is implemented by monitoring the fault indicator bearing frequencies and harmonics, calculated using the bearing dimensions and …
Detection Of Static Eccentricity For Permanent Magnet Synchronous Motors Using The Coherence Analysis, Mehmet Akar, Sezai̇ Taşkin, Şahi̇n Serhat Şeker, İlyas Çankaya
Detection Of Static Eccentricity For Permanent Magnet Synchronous Motors Using The Coherence Analysis, Mehmet Akar, Sezai̇ Taşkin, Şahi̇n Serhat Şeker, İlyas Çankaya
Turkish Journal of Electrical Engineering and Computer Sciences
This paper reports on work to detect the static eccentricity faults for permanent magnet synchronous motor (PMSM) using spectral analysis methods. Measurements are carried out by collecting the stator current and voltage, torque and speed for healthy and faulty cases of the motor. Static eccentricity case is formed by changing the rotor position in the manner of sliding the shaft on a horizontal axis. As a result of the spectral analysis for the motor currents, side band effects appeared at around the fundamental frequency are determined as a most important indicator of the eccentricity. In addition to this determination, the …