• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.3
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• pp.75-84
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• 2005

Since an unexpected fault of induction motor drive systems can cause serious troubles in many industrial applications, which the technique is required to diagnose faults of a voltage-fed PWM inverter for induction motor drives. The considered fault types are rectifier diodes, switching devices and input terminals with open-circuit faults, and the signal for diagnosis is derived from motor currents. The magnitude of dq-current trajectory is used for the feature extraction of a fault and PCA LDA are applied to diagnose. Also, we show results with respect to the execution time because of the possibility to use that a diagnosis software is embedded in the controllers of medium and small size induction motors drive for real-time diagnosis. After we performed various simulations for the fault diagnosis of the inverter, the usefulness of proposed algerian was verified.

• Journal of Advanced Navigation Technology
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• v.16 no.1
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• pp.1-7
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• 2012

In this research, a single-axis attitude control test bed is developed, and simulation and tests experiments are performed, as a preliminary research of a quad-rotor aerial vehicle development. A single-axis test bed with seesaw configuration is manufactured using two motors and propellers, and the aerodynamic parameters are derived by thrust tests. The response of the system is estimated with Matlab/Simulink, and experiments are performed with attitude control computer and an attitude sensor onboard the test bed. Comparing the results of simulated and tested data, factors of steady-state errors during experiments are found, and performances of used attitude control algorithm and the control computer were verified. In these process, essential preliminary data for attitude control of a quad-rotor unmanned aerial vehicle were acquired.

• Journal of Power Electronics
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• v.6 no.1
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• pp.38-44
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• 2006

In this paper, a speed sensorless control for an ultrasonic motor (USM) using a neural network (NN) is presented. In the proposed method, rotor speed is estimated by a three-layer NN which adapts nonlinearities associated with load torque and motor temperature into control. The intrinsic properties of a USM, such as high torque for low speeds, high static torque, compact size, etc., offer great advantages for industrial applications. However, the speed property of a USM has strong nonlinear properties associated with motor temperature and load torque, which make accurate speed control difficult. These properties are considered in designing a control method through the application of mathematical models. In these strategies, a detailed speed model of the USM is required which makes actual applications impractical. In the proposed method, a three-layer NN estimates the speed of the USM from the drive frequency, the root mean square value of input voltage and the surface temperature of the USM, where no mechanical speed sensor is needed. The NN speed based estimator enables inclusion of variations in driving conditions due to input signals of the NN involved during the driving state of the USM. The disuse of sensors offers many advantages on both the cost and maintenance front. Moreover, the model free sensorless control method offers practical controller construction within a small number of parameters. To validate the proposed speed sensorless control method for a USM, experiments have been executed under several conditions.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1258-1260
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• 2005

Superconducting synchronous motors and generators have the field coil composed of superconductor with almost zero resistance at superconducting state. Therefore, co or loss at the conventional field coil is eliminated and the superconducting machine gets higher efficiency. The armature coil of the superconducting machine is composed of cower wire and supported by non-magnetic material such as FRP(Fiber Reinforced Plastic). Although a fully-superconducting machine with superconducting armature coil has been researched, it was not developed toward industrial application because of AC transporting loss and difficulty in construction of the cooling structure and so on. This paper contains the design procedure of a 1 MW superconducting synchronous motor using high-temperature superconductor only for the field coil. Especially, the armature coil is designed by water-cooling in order to dissipate Joule heat easily. Moreover, 3-dimensional electromagnetic design is conducted to get a proper design result and reduce design errors from 2-dimensional approach.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.691-697
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• 2006

Induction motors are critical components in industrial process. So there are many research in the condition based maintenance, online monitoring system, and fault detection. This paper presents a scheme on the detection and diagnosis of the three-phase squirrel induction motor under unbalanced voltage, broken rotor bar, and a combination of these two faults. Actually one fault happen in operation, it influence other component in motor or cause another faults. Accordingly it is useful to diagnose and detect a combination fault in induction motor as well as each fault. The proposed fault detection and diagnosis algorithm is based on the stator currents from the squirrel induction motor and simulated with the aid of Matlab Simulink.

• Journal of Powder Materials
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• v.26 no.2
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• pp.146-155
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• 2019

Rare earth magnets are the strongest type of permanent magnets and are integral to the high tech industry, particularly in clean energies, such as electric vehicle motors and wind turbine generators. However, the cost of rare earth materials and the imbalance in supply and demand still remain big problems to solve for permanent magnet related industries. Thus, a magnet with abundant elements and moderate magnetic performance is required to replace rare-earth magnets. Recently, $a^{{\prime}{\prime}}-Fe_{16}N_2$ has attracted considerable attention as a promising candidate for next-generation non-rare-earth permanent magnets due to its gigantic magnetization (3.23 T). Also, metastable $a^{{\prime}{\prime}}-Fe_{16}N_2$ exhibits high tetragonality (c/a = 1.1) by interstitial introduction of N atoms, leading to a high magnetocrystalline anisotropy constant ($K_1=1.0MJ/m^3$). In addition, Fe has a large amount of reserves on the Earth compared to other magnetic materials, leading to low cost of raw materials and manufacturing for industrial production. In this paper, we review the synthetic methods of metastable $a^{{\prime}{\prime}}-Fe_{16}N_2$ with film, powder and bulk form and discuss the approaches to enhance magnetocrystalline anisotropy of $a^{{\prime}{\prime}}-Fe_{16}N_2$. Future research prospects are also offered with patent trends observed thus far.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.135-141
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• 2021

Interest is growing in the design and development of square wave driven BLDC permanent magnet motors suitable for industrial automation, and the development of position detection circuits and drivers. However, this motor is somewhat limited in its application despite the price and functional advantages due to the decrease in efficiency due to switching loss and vibration and noise. In the process of designing and assembling a BLDC motor, the magnetic pole angle is not uniform or the magnetic flux distribution is distorted due to problems in magnetic circuit design or product non-uniformity in the assembly process. Therefore, these things cause position detection deviation and deteriorate the motor characteristics. In addition, the sine wave driven BLDC system can operate stably only when the signal generated from the position sensor is accurately fed back to the driver. However, since the generated signal cannot perform stable position detection due to the occurrence of DC offset component due to magnetic flux density deviation or magnetization technology, which is an external influence, this study intends to study the proposed circuit that can remove the DC offset component.

• Journal of Platform Technology
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• v.8 no.2
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• pp.22-31
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• 2020

The construction and operation of industrial automation has been actively taking place from manufacturing plan to production for improving operational efficiency of production line and flexibility of equipment. ISO/TC184 is standardizing on operating methods that can share information of programmable device controllers such as PLC and IoT that are geographically distributed in the production line. In this study, the design of the cell controller consists of PLC group and IoT group that perform signals such as temperature sensors, gas sensors, and pressure sensors for thermal processes and corresponding motors or valves. The operation and analysis of the cell controller were performed using SDN(Software Defined Network) and the three types of process services performed in thermal processes are real-time transmission service, loss-sensitive large-capacity transmission service, and normal transmission service. The simulation result showed that the average loss rate improved by about 17% when the traffic increased before and after the application of the SDN route technique, and the delay in the real-time service was as low as 1 ms.

• The Research Journal of the Costume Culture
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• v.30 no.1
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• pp.88-101
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• 2022

Molybdenum is used in electrical contacts, industrial motors, and transportation materials due to its remarkable ability to resist heat and corrosion. It is also used to flame coat other metals. This study investigated, the thermal characteristics of the molybdenum sputtered material, such as electrical conductivity, and stealth effects on infrared thermal imaging cameras. To this end, molybdenum sputtered samples were prepared by varying the density of the base sample and the type of base materials used. Thereafter, the produced samples were evaluated for their surface state, electrical conductivity, electromagnetic field characteristics, thermal characteristics, stealth effect on infrared thermal imaging cameras, and moisture characteristics. As a result of infrared thermal imaging, the molybdenum layer was directed towards the outside air, and when the sample was a film, it demonstrated a greater stealth effect than the fabric. When the molybdenum layer was directed to the outside air, all of the molybdenum sputtering-treated samples exhibited a lower surface temperature than the "untreated sample." In addition, as a result of confirming electrical properties following the molybdenum sputtering treatment, it was determined that the film exhibited better electrical conductivity than the fabric. All samples that were subjected to molybdenum sputtering exhibited significantly reduced electromagnetic and IR transmission. As a result, the stealth effect on infrared thermal imaging cameras is considered to be a better way of interpreting heat transfer than infrared transmission. These results are expected to have future applications in high-performance smartwear, military uniforms, and medical wear.

• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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• pp.65-70
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• 2022

In manufacturing and semiconductor industries, transfer robots increase productivity through accurate and continuous work. Due to the nature of the semiconductor process, there are environments where humans cannot intervene to maintain internal temperature and humidity in a clean room. So, transport robots take responsibility over humans. In such an environment where the manpower of the process is cutting down, the lack of maintenance and management technology of the machine may adversely affect the production, and that's why it is necessary to develop a technology for the machine failure diagnosis system. Therefore, this paper tries to identify various causes of failure of transport robots that are widely used in semiconductor automation, and the Prognostics and Health Management (PHM) method is considered for determining and predicting the process of failures. The robot mainly fails in the driving unit due to long-term repetitive motion, and the core components of the driving unit are motors and gear reducer. A simulation drive unit was manufactured and tested around this component and then applied to 6-axis vertical multi-joint robots used in actual industrial sites. Vibration data was collected for each cause of failure of the robot, and then the collected data was processed through signal processing and frequency analysis. The processed data can determine the fault of the robot by utilizing machine learning algorithms such as SVM (Support Vector Machine) and KNN (K-Nearest Neighbor). As a result, the PHM environment was built based on machine learning algorithms using SVM and KNN, confirming that failure prediction was partially possible.