Manop, Chalermchat

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Manop, Chalermchat
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Manop, C.
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chalermchat.ma@kmitl.ac.th

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    Design and Testing of Low Loss Distribution Transformer for Non-Linear Loading Current
    (2018-07-02)
    Tandeaw, P.
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    Manop, C.
    ;
    Jirasuwankul, N.
    Distribution transformers are typically designed to operate under linear loading current. Nowadays, an emerging of modern electric loads that equipped with power conversion devices, it is inevitable that, the transformers are subjected to supply non-linear current. Those are resulting in a considerable increment of heat loss, temperature rising and shortening of insulation lifespan. In case of planning for retrofit or new utility system design, replacing conventional transformer with the low loss one is introduced. This paper therefore proposes a design and testing of low loss transformer using K-Factor and modified winding eddy current loss (WEC). Test results show that efficiency and temperature rise of the new design outperforms conventional one under standard testing of linear and non-linear loads.
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    A lab-scale heliostat positioning control using fuzzy logic based stepper motor drive with micro step and multi-frequency mode
    (2017-08-23)
    Jirasuwankul, N.
    ;
    Manop, C.
    This paper proposes positioning control technique for a lab-scale heliostat by application of hybrid stepper motors and fuzzy logic controllers. Steady state tracking error has been kept minimal by micro step drive together with speed control by multi stepping rate adjustment. By supportive video streaming device and image processing, a reflected image of illuminant area on the target is captured and analyzed, an obtaining position error in azimuth and altitude angles are real-time fed to the fuzzy controllers. As a result, the closed loop tracking is formulated and steady state error can then be minimized. Simulation and experimental results confirm the proposed technique.
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    Air-gap power and rotor loss estimation for induction motor efficiency monitoring based on Kalman filtering
    (2013-01-01)
    Jirasuwankul, N.
    ;
    Manop, C.
    This paper presents a technique of induction motor's efficiency monitoring based on air-gap power and rotor loss estimation by Kalman filtering. A simplified model of three phase induction motor, with equivalent circuit of five elements, has been tested by the proposed technique with varying load torque and power to represent practical operations. Good agreement between the simulation and experimental results are found in a normal operating range of load torque and power. © 2013 IEEE.
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    Fault detection and protection of three-phase induction motor using Eigen based analysis
    (2016-10-24)
    Stapornirun, Somsak
    ;
    Tangsiriworakul, Chanwit
    ;
    Manop, Chalermchat
    This research presents the design and the implementation of a system for detecting and preventing external faults of 3 phase induction motor using Eigen based analysis, in order to prevent faults in various pattern and reduce the complexity of data processing. The 6 inputs are composed of three-phase voltage and current signals for the induction motor. These inputs will be calculated for the root mean square values before the Eigen based analysis and Euclidean Distance calculation. These values are comparable to which of the normal condition of the induction motor, in order to identify the faults in 6 conditions of Single Phase, Over Voltage, Under Voltage, Over Load, Unbalance Voltage and Locked Rotor. The software is designed by MATLAB program connecting with the DAQ card for controlling the 6 signal inputs receiving and sending an output signal to control power supply relay to the induction motor. After the experiment under the various loading conditions was conducted, the system can detect and prevent the external faults in 6 conditions satisfactorily.
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    The classification of regular and defected low voltage XLPE cable by using polarization and depolarization current method
    (2017-10-19)
    Singhasivanon, J.
    ;
    Manop, C.
    ;
    Pattanadech, N.
    ;
    Jirasuwankul, N.
    Electric cable is an important part of utility power and distribution system. In order to keep the system operation safely and reliable, acceptance testing for cable is necessary not only inservice but also manufacturing process. This paper proposes a novel testing technique which is able to classify the difference between normal and defective low voltage XLPE cable, namely polarization and depolarization current technique (PDC). In this study, PDC testing of low voltage XLPE cable was performed comparatively among five different cases: cable contaminated with a piece of paper, case 2 : cable contaminated with a piece of plastic, case 3 : cable contaminated with grease, case 4 : cable contaminated with a piece of copper, and case 5 : Eccentric conductor cable. With environmental control of the testing process, the test results show the polarization current of the defective contaminated cable with copper is higher than that of the regular one, whereas it is lower than that of the defective one with paper, plastic and grease. It is also found that there was indistinctive of PDC in case of copper contaminated and eccentric conductor cable.
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    SVM-based stator fault diagnosis for induction motors using DQ0 voltage components
    (2010-10-01)
    Manop, Chalermchat
    ;
    Kinnares, Vijit
    ;
    Chunwiphat, Suphot
    This paper presents a new technique for diagnosis of stator winding shorted turns in three phase induction motors using support vector machine (SVM) as a classifier in conjunction with a voltage signature analysis as feature extraction. The proposed dqO voltage components related to three phase voltages are obtained by using Park's transformation. Unlike general dqO quantity, the required dq components are considered from only harmonics in a certain range resulted from the stator shorted turn fault whilst the required zero component is determined from the fundamental voltage excitation only. The procedure for finding the harmonic spectrum associated with the stator fault employs a FFT technique together with digital signal processing in order to enlarge such harmonics to be easily detected. The data of d, q and zero components will be used as the input features for a SVM classification and diagnosis. In order to confirm that the dqO voltage components could be used as quantity for identifying the stator fault, patterns of dqO voltage components in three-dimension are plotted. The obtained trajectories are obviously different depending on the severity of the shorted turn fault. In training and testing with a multiclass-SVM classification, the good accuracy is obtained under various load conditions for both healthy and stator fault conditions. The SVM classification performance of the proposed method has high accuracy greater than 98% comparable to other feature extraction processes such as a motor current signature method (MCSA) but the number of training data and features for the proposed technique are less. © 2010 ICIC International.