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Öğe Analysis of Rotor Faults Effects on Submersible Induction Motor' Efficiency(INT ASSOC ENGINEERS-IAENG, 2013) Arabaci, Hayri; Bilgin, OsmanThis paper analyzes effects of squirrel cage faults on submersible induction motors efficiency at steady-state condition. There are a lot of studies about effects of the cage faults on motor performance. Especially, the effects of the cage faults on the motor parameters such as current, torque and speed are well known. Unlike the literature, cage fault effects on efficiency are analyzed in this study. Furthermore, fluctuations and mean value changes resulting from the rotor faults are ranked according to size of these faults. Healthy and five different faults were investigated by using 10 HP, 25 HP, 30 HP and 50 HP submersible induction motors in both simulations and experiments. Time stepping finite element method solution was used to compute motor quantities in the simulation. Good agreement was achieved between simulation and experimental results. The effects of rotor faults on motor efficiency were clearly ranked according to size of faults.Öğe Application of a hybrid evolutionary technique for efficiency determination of a submersible induction motor(TUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEY, 2011) Mutluer, Mumtaz; Bilgin, OsmanElectric motors are the largest consumers of electricity in plants and induction motors constitute nearly two-thirds of them. The replacement of in-service induction motors with more efficient ones is a very important strategy for energy savings and consequently nearly 30 different methods have been used to determine the efficiency of induction motors in the last 2 decades. This paper aims to develop the efficiency determination of a 20 Hp submersible induction motor. Due to getting perfect efficiency of the submersible induction motor, a robust hybrid evolutionary optimization technique, which consists of a genetic algorithm and simulated annealing, is used. The obtained results are compared with genetic algorithm and torque gauge result values and dramatically significant results of our proposed algorithm are observed.Öğe Application of Finite Element Method to Determine the Performances of the Line Start Permanent Magnet Synchronous Motor(ELSEVIER SCIENCE BV, 2015) Kul, Seda; Bilgin, Osman; Mutluer, MumtazIn this paper, low power line start permanent magnet synchronous motor (LSPMSM) is analyzed and simulationed by finite element method using ANSYS RMXPRT and Maxwell 2D/3D modeling software. Parameters of three motor are changed, are modeled than put to the simulation. While the motors are analyzed, motor dimensions aren't changed. After motors are modeled by RMXPRT, the models are transposed to maxwell and observed the magnetic field distribution. The torque and efficiency curve are acquired and compared with each other. Consequently, the results are evaluated in terms of feasibility for the industrial area in terms of efficiency and torque (C) 2015 The Authors. Published by Elsevier Ltd.Öğe Automatic Detection and Classification of Rotor Cage Faults in Squirrel Cage Induction Motor(Springer London Ltd, 2010) Arabacı, Hayri; Bilgin, OsmanThe detection of broken rotor bars and broken end-ring in three-phase squirrel cage induction motors by means of improved decision structure. The structure consists of current signal analysis (CSA), Artificial Neural Network (ANN) and diagnosis algorithm. Effects of broken bars and end-ring on current signal and feature extraction are in the CSA. The rotor cage faults are classified by using ANN. And result matrixes of ANN are considered two different ways for diagnosis. Then the diagnoses are compared with each other. In this study six different rotor faults, which are one, two, three broken bars, bar with high resistance, broken end-ring and healthy rotor, are investigated. The effects of different rotor faults on current spectrum, in comparison with other fault conditions, are investigated by analyzing side-bands in current spectrum. To reduce bad effects of changing of distance between the side-band and main component on the detection and classification of the faults, the spectrum is achieved with low definition. Thus, the improved decision structure diagnoses faulted rotors with 100% accuracy and classified rotor faults 98.33% accuracy.Öğe Comparison of stochastic optimization methods for design optimization of permanent magnet synchronous motor(SPRINGER LONDON LTD, 2012) Mutluer, Mumtaz; Bilgin, OsmanThis study presents design optimization of permanent magnet synchronous motor by using different artificial intelligence methods. For this purpose, three stochastic optimization methods-genetic algorithm, simulated annealing, and differential evolution-were used. Motor design parameters and efficiency results obtained by the artificial intelligence methods were compared with each other. The results were later checked by finite element analysis. Consequently, the motor efficiencies obtained from the algorithms have high accuracy. Approaches strategies of the artificial intelligence algorithms are quite sufficient and remarkable for design optimization of permanent magnet synchronous motor. The differential evolution is better and more reliable optimization method nevertheless.Öğe Cost optimization of submersible motors using a genetic algorithm and a finite element method(SPRINGER LONDON LTD, 2007) Cunkas, Mehmet; Akkaya, Ramazan; Bilgin, OsmanThis paper presents an optimal design method to optimize cost of three-phase submersible motors. The optimally designed motor is compared with an industrial motor having the same ratings. The motor design procedure consists of a system of non-linear equations, which imposes induction motor characteristics, motor performance, magnetic stresses, and thermal limits. The genetic algorithm (GA) is used for cost optimization, and a software algorithm has been developed. As a result of the realized optimization, besides the improvements on the motor cost, motor torque improvements have also been acquired. The 2-D finite element method (FEM) is then used to confirm the validity of the optimal design. Computer simulation results are given to show the effectiveness of the proposed design process that can achieve a good prediction of the motor performance. Through the studies accomplished, it has been observed that submersible induction motors' torques and efficiencies improve, their length reduces, and hence some materialÖğe Design Optimization of Pmsm by Particle Swarm Optimization and Genetic Algorithm(2012) Mutluer, Mümtaz; Bilgin, OsmanOne of the electric power researches is the design optimization studies of permanent magnet synchronous motors. The main advantages of design optimizations of permanent magnet synchronous motors are to contribute to comfort, cost, and especially to energy savings. Although absence of rotor windings affects efficiencies of permanent magnet synchronous motors, stringent selection of values of geometrical design parameters affects the efficiency. Artificial intelligence techniques are satisfactory in choosing of design parameters of electric motors. This study aims to provide the design optimization of surface mounted permanent magnet synchronous motor thus. First of all geometrical design parameters of the motor were identified and then preliminary analytical design and design optimization by using genetic algorithm and particle swarm algorithm were studied. The obtained efficiency results were compared with each others and the results is satisfactory. © 2012 IEEE.Öğe Detection of Rotor Bar Faults by Using Stator Current Envelope(INT ASSOC ENGINEERS-IAENG, 2011) Arabaci, Hayri; Bilgin, OsmanThe paper presents detection of rotor bar faults at steady state operation in squirrel cage induction motor by using stator current envelope. Three different rotor faults and healthy motor conditions were investigated in experiments. One of the stator currents has been used in the investigation of effects of rotor faults on the current envelope. The ratios of fluctuation of the envelope were used as feature of fault conditions for diagnosis. In the literature a lot of studies are available about diagnosis and detection rotor many different analysis and feature extraction methods such as motor current signature analysis (MCSA), fast Fourier transform (FFT). Unlike the literature, in the present study the stator current envelopes are used. The use of the current envelope does not affect the performance of the fault detection, while requiring much less computation and low cost in implementation, which would make it easier to implement in embedded systems for condition monitoring of motor.Öğe The detection of rotor faults by using Short Time Fourier Transform(IEEE, 2007) Arabaci, Hayri; Bilgin, OsmanIn this paper an experimental study detecting of rotor faults in three-phase squirrel cage induction motors by means of Short Time Fourier Transform (STFT) is presented. The frequency spectrum of motor line current is exploited for the detection. By obtaining a number of frequency spectrums from a current data with STET and averaging these spectrums, faults are diagnosed instead of Fast Fourier Transform frequently applied at the detection of broken rotor faults in the literature. Five different faulted rotors are investigated. These faults are one bar with high resistance of the rotor, one broken bar of the rotor, two broken bars of the rotor, three broken bar of the rotor and broken end ring of the rotor. Artificial Neural Network is used for classification of faults. Test results show that this method increase the accuracy of the fault diagnose.Öğe The detection of rotor faults in the manufacturing of submersible induction motor(IEEE, 2007) Arabaci, Hayri; Bilgin, Osman; Urkmez, AbdullahIn this study, rotor faults detection in submersible induction motors which is used at deep well submersible pumps is presented by analyzing stator current. In some production squirrel cage rotor bars are welded to end rings by argon welding. While the welding sometimes some bars are not connected to end rings ore bad connection have been occurred. This affects the motor performance. For not preventing the production speed motor tests should be made quickly. In this study practical results are taken from POLMOT factory which produce submersible induction motors. When the motor construction is finished its robustness is tested with no load test. Their stator current time frequency domain is made and its current spectrum is investigated. According to current spectrum analysis its fault and robustness is determined. For classification Artificial Neural Network (ANN) is used. A decision mechanism that uses ANN result matrixes is occurred to detect faulted rotors.Öğe The detection of rotor faults using artificial neural network(IEEE, 2006) Arabaci, Hayri; Bilgin, OsmanThe detection of broken rotor bars in tree-phase squirrel cage induction motors by means of current signature analysis is presented. In order to diagnose faults, a Neural Network approach is used. At first the data of different rotor faults are achieved. The effects of different rotor faults on current spectrum, in comparison with other fault conditions, are investigated via calculating Power Spectrum Density (PSD). Training the Neural Network discern between "healthy" and "faulty" motor conditions by using experimental data in case of healthy and faulted motor. The test results clearly illustrate that the stator current signature can be used to diagnose faults of squirrel cage rotor.Öğe Diagnosis of Broken Rotor Bar Faults by Using Frequency Spectrum of Stator Current Envelope(IEEE, 2012) Arabaci, Hayri; Bilgin, OsmanThe paper presents squirrel cage induction motor rotor bar faults detection and classification by using stator current envelope at steady state operation. One of the stator currents has been used in the investigating of effects of rotor faults on the current envelopes. Fluctuations of the envelope were used as features of faults conditions for diagnosis. For feature extraction, frequency spectrum of the envelope of current was obtained by fast Fourier Transform (FFT). Significant picks in the spectrum were used to discern "healthy" and "faulty" motor conditions. The motor conditions were classified by Artificial Neural Network (ANN). In experiments three different rotor faults and healthy motor conditions were investigated by 30 HP, 8 '', with 18 bars, 380V, 2 poles and 50 Hz squirrel cage submersible induction motor. The proposed decision structure detects and classifies rotor bar faults with 100% accuracy.Öğe The Effect of Magnet Temperature on Speed, Current and Torque in PMSMs(IEEE, 2016) Bilgin, Osman; Kazan, Fatih AlpaslanIn this study, the effect of magnet temperature on speed, current and torque in permanent magnet synchronous motor was investigated. First, the demagnetization curves of Neomag S 28VC class magnet related to different temperatures, which was used for MCS06C41 coded motor of Lenze Company, were approached. A mathematical expression was achieved to calculate the remanence value for any temperature using these curves and curve fitting method. Then, a simulation was made according to the field oriented vector control method in MATLAB/Simulink using real motor and driver parameters. The mathematical expression that gives the change of magnetic flux related to the temperature influence was included in the modelling. In this way, the change of the speed, current and torque for different magnet temperatures were made observable. Six simulations were made with 25 degrees C increase from 25 degrees C to 150 degrees C to observe the effect of the temperature on the motor much better. The simulation results have clearly demonstrated the effects of the increase of the magnet temperature especially on the current and torque.Öğe Efficiency Analysis of Submersible Induction Motor with Broken Rotor Bar(SPRINGER, 2014) Arabaci, Hayri; Bilgin, OsmanThis study analyzes effects of squirrel cage faults on submersible induction motors efficiency at steady-state condition. There are a lot of studies about effects of the cage faults on motor performance. Especially, the effects of the cage faults on the motor parameters such as current, torque and speed are well known. Unlike the literature, cage fault effects on efficiency are analyzed in this study. Furthermore, fluctuations and mean value changes resulting from the rotor faults are ranked according to size of these faults. Healthy and five different faults were investigated by using 10, 25, 30 and 50 HP submersible induction motors in both simulations and experiments. Time stepping finite element method solution was used to compute motor quantities in the simulation. Good agreement was achieved between simulation and experimental results. The effects of rotor faults on motor efficiency were clearly ranked according to size of faults.Öğe An intelligent design optimization of a permanent magnet synchronous motor by artificial bee colony algorithm(TUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEY, 2016) Mutluer, Mumtaz; Bilgin, OsmanThe artificial bee colony algorithm is one of the latest stochastic methods based on swarm intelligence. The algorithm simulates the foraging behavior of honeybees. The structure of the algorithm is quite simple and its coding is very easy. This paper proposes a design optimization based on geometrical variables to obtain a highly efficient surface mounted permanent magnet synchronous motor with concentrated winding by use of the artificial bee colony algorithm. Input parameters for the algorithm are the geometrical variables of the motor. This approach is more advantageous than finite element analysis requiring a long period of time. Results of the artificial bee colony algorithm are compared with results of a genetic algorithm and checked with a commercial design program. The results emphasize the effectiveness of the algorithm on the design optimization of the permanent magnet synchronous motor.Öğe Neural Network Classification and Diagnosis of Broken Rotor Bar Faults by Means of Short Time Fourier Transform(INT ASSOC ENGINEERS-IAENG, 2009) Arabaci, Hayri; Bilgin, OsmanIn this paper an experimental study of classification and diagnosis of different number of broken rotor bars and broken end-ring in the three-phase squirrel cage induction motors is presented. Six different faulted rotors are investigated. These faults are one, two, three broken bars, broken end-ring, a bar with high resistance and healthy rotor. The base structure of the study consist of current signal analysis (CSA), feature extraction, Artificial Neural Network (ANN) and diagnosis algorithm. The motor current signal is used for obtaining of effects of broken bars and end-ring in the rotor. To get sight of the effects the current signal that is in the time domain is transformed time-frequency domain via Short Time Fourier Transform (STFT). And the spectrums are averaged and normalized on the time axis. The rotor cage faults are classified with ANN by using these spectrums. And result matrixes of ANN are considered improved decision structure. Thus the faulted rotors are diagnosed at 100% accuracy and classified 98,33% accuracy.Öğe A novel motor speed calculation method using square wave speed sensor signals via fast Fourier transform(TUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEY, 2012) Arabaci, Hayri; Bilgin, OsmanThis paper presents a novel motor speed measurement method and experimental results using the fast Fourier transform (FFT). Motor speed is obtained using the square wave output signal of a speed sensor. In the proposed method, the speed can be measured in a wide range, and transient speed changes can also be clearly observed. The experiments were conducted during start-up and in steady state. The sampled speed data were transformed to frequency spectrums using the FFT. The frequency, which corresponds to the maximum amplitude in the spectrum, was used to calculate the motor speed. The test results show that the proposed method is very useful.Öğe Parameter determination of induction machines by hybrid genetic algorithms(SPRINGER-VERLAG BERLIN, 2007) Mutluer, Muemtaz; Bilgin, Osman; Cunkas, MehmetIn general, a genetic algorithm combined with other algorithms (e.g. tabu search, simulated annealing, etc.) is well known to be a powerful approach. In this paper, an efficient hybrid approach containing local search and genetic algorithms is presented. The purpose of the using local search mechanisms is to provide better the solution quality and to increase the convergence speed. It is demonstrated that the performance of the proposed algorithms is significantly better than the conventional genetic algorithm methods.Öğe Remote monitoring and diagnostic system of PLC controlled an elevator using SCADA [PLC ile kontrol edilen bir asansörün SCADA ile i?zlenmesi ve ariza takibi](2010) Bilgin, Osman; Altun, Yasin; Mutluer, MümtazElevators such devices that should have minimum fault, maximum passenger comfort and should be very fast. Passengers in faulted elevators should be rescued in a very short time and should be renovated as soon as possible. In this case the condition of the elevator and cabin position should be observed. In this study an elevator automation system designed and constructed which contain remote monitoring the cabin motion dynamically at computer screen with a SCADA program. At the same time it also shows the cabin position and type of the faults.Öğe Rotor Bar Fault Diagnosis by Using Power Factor(INT ASSOC ENGINEERS-IAENG, 2011) Arabaci, Hayri; Bilgin, Osman; Urkmez, AbdullahThe paper presents detection and classification of rotor bar faults at steady state operation in squirrel cage induction motor by using power factor. One phase current and voltage of the stator coils were used to calculate the power factor. To investigate effects of rotor faults on the power factor, its frequency spectrum was obtained by fast Fourier Transform (FFT). Significant picks in the spectrum were used to discern "healthy" and "faulty" motor conditions. The motor conditions were classified by Artificial Neural Network (ANN). In experiments three different rotor faults and healthy motor conditions were investigated by 30 HP, 8", with 18 bars, 380V, 2 poles and 50 Hz squirrel cage submersible induction motor. The proposed decision structure detects and classifies rotor bar faults with 100% accuracy.
