• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.2
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• pp.78-83
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• 2016

The development of an exclusive 8-axis multi-tasking machine to finish multiple cutting processes by a single piece of power equipment for securing the high-precision machining and high productivity of the series of shafts (a core part of the automotive powertrain that delivers engine power) is needed. The rigidity of the structure must be improved and the weight of the structure must be reduced to develop a multi-tasking machine with high precision and high productivity. In this paper, we perform a static structural analysis of the initial design of the multi-tasking machines and compare the results of the multi-tasking machines improved by the reinforced design and the results of the initial one. According to the results of the structural analysis, the rigidity of the reinforced machine was increased and the overall weight was decreased. Therefore, the productivity was increased.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.662-668
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• 2015

This paper presents an improved predictive control of an induction machine fed by a matrix converter using N-switching vectors as the control action during a complete sampling period of the controller. The conventional model predictive control scheme based matrix converter uses a single switching vector over the same period which introduces high torque ripple. The proposed switching scheme for a matrix converter based model predictive control of an induction machine drive selects the appropriate switching vectors for control of electromagnetic torque with small variations of the stator flux. The proposed method can reduce the ripple of the electrical variables by selecting the switching state as well as the method used in the space vector modulation techniques. Simulation results are presented to verify the effectiveness of the improved predictive control strategy for induction machine fed by a matrix converter.

• Journal of Power Electronics
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• v.12 no.5
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• pp.758-768
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• 2012

This paper presents the modeling and position-sensorless vector control of a dual-airgap axial flux permanent magnet (AFPM) machine optimized for use in flywheel energy storage system (FESS) applications. The proposed AFPM machine has two sets of three-phase stator windings but requires only a single power converter to control both the electromagnetic torque and the axial levitation force. The proper controllability of the latter is crucial as it can be utilized to minimize the vertical bearing stress to improve the efficiency of the FESS. The method for controlling both the speed and axial displacement of the machine is discussed. An inherent speed sensorless observer is also proposed for speed estimation. The proposed observer eliminates the rotary encoder, which in turn reduces the overall weight and cost of the system while improving its reliability. The effectiveness of the proposed control scheme has been verified by simulations and experiments on a prototype machine.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.3
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• pp.406-415
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• 2024

As the equipment of the military has become more advanced and expensive, the cost of securing spare parts is also constantly increasing along with the increase in equipment assets. In particular, forecasting demand for spare parts one of the important management tasks in the military, and the accuracy of these predictions is directly related to military operations and cost management. However, because the demand for spare parts is intermittent and irregular, it is often difficult to make accurate predictions using traditional statistical methods or a single statistical or machine learning model. In this paper, we propose a model that can increase the accuracy of demand forecasting for irregular patterns of spare parts demanding by using a combination of statistical and machine learning algorithm, and through experiments on Cheonma spare parts demanding data.

• The korean journal of orthodontics
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• v.28 no.1 s.66
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• pp.29-41
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• 1998

Despite orthodontic treatment(tooth moving) is dynamic act many orthodontists have used mainly static evaluation method for evaluating effectiveness of the orthodontic appliances. They want to find which is better appliance, especially in the treatment results and treatment period when they chose one appliance from sugessted appliances for obtaining same treatment goal. The author and colleagues invented and manufactured new machine for getting information about the relative effectiveness from many suggested orthodontic appliances and we named it Calorific machine. We used this Calorinc machine to find the relative differences about tooth moving mechanism and tooth moving time between the Burstone's PLA(single force mechanism) and Molar-up's PLA(couple mechanism) for correcting the posterior cross bite. We measured the distance of tooth moving on the occlusal X-ray film and recorded the moving time of the anchored(control elctro-thermal tooth) and lingually tipped lower second molars(experimental electro-thermal tooth) and then processed paired t-est by SAS program. The results were as follows. 1. Molar-up's PLA showed more extrusive and horizontal movement than Burstone's PLA at the lingually tipped molar(p=0.0000). 2. There is no finding of tooth movement by Molar-up's PLA at the uprighted molar(p=o.3475) but Burstone's PLA showed a little change(0.2 m) at the same molar(p=0.0001). 3. Burstone's PLA took 17.8 minutes for tooth moving but Molar-up's PLA took only 3.8 minutes(p=0.0001)

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.5
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• pp.854-859
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• 2010

Distribution Automation System(DAS) is designed to improve operational efficiency by acquisition and control of remote data using its components such as central computation units, communication network and feeder remote terminal units. A conventional human machine interface of the DAS adopts a schematic diagram which is made by drawing power equipments on the geographic information system map. The single line diagram is more useful than the schematic diagram for the main tasks of distribution system operation such as protective relay coordination, service restoration and loss minimization. Since the configuration of the distribution line is changed according to the relocation of the open tie switches, the auto-drawing algorithm based on the connection between the sections and the switches is an essential technique. This paper proposes a new auto-drawing algorithm for a single line diagram of distribution systems based on tertiary tree and collision avoidance method. The feasibility of the proposed algorithm has been testified for various cases using practical distribution system with 12 feeders.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.406-411
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• 2003

It is clearly demonstrated that deeper cups could be formed by single and double stretch-drawings from smaller circular blanks due to such wall-thinning action than in the usual deep-drawing of larger blanks. From this fact, it is emphasized that the deep-drawability of a sheet metal Is not evaluated simply by the conventional L.D.R (limiting drawing ratio), but the depth of the drawn cup should also be taken into account. Many experimental data about various metals and thicknesses given in this paper offer a valuable information in this process for more general use which recommends to replace the conventional deep-drawing process by the stretch-drawing process both for single and double operations. In the single stretch-drawing, it is also confirmed that a deeper cup can be produced by raising the blank-holding force at later stage of operation.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1995.10a
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• pp.76-81
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• 1995

MgO single crystal is widely used as a the material of high temperature resistance, but is difficult to grind because of brittleness and crack generation. Therefore, superabrasive diamond wheel is required for mirror like grinding of this material. This study describes a newly proposed optimum in-process electrolytic dressing system for carrying out effective dressing of superbrasive diamond wheel. Using this system the grinding surface of MgO single crystal was improved, the grinding force was very l9ow and crack was removed. In conclusion, this system is good to obtain the efficient grinding and mirror-like grinding without crack of MgO single crystal.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.4
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• pp.331-336
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• 2005

With increasing emphasis on non-conventional energy systems and autonomous power generation, development of improved and appropriate generating systems has recently taken on greater significance. This paper describes the performance analysis of a single phase self-excited induction generator (SEIG), suitable for autonomous/standby power systems. The system is also appropriate for wind energy systems and small portable systems. Both windings of the induction machine, the main and the auxiliary, are utilized. One winding will be devoted to the supply excitation current only, by being connected to the excitation capacitor, while the load is connected across the other winding. As the design of excitation, the minimum of self-excited capacitor connected auxiliary winding is determined as the suitable value using a circuit equation of auxiliary winding. For the steady state analysis, the equivalent circuit of the single-phase induction generators is used as a basis for modeling using the double-revolving field theory. The validity of the designed generator system is confirmed by experimental and computed results.

• Journal of the Korea Society of Computer and Information
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• v.22 no.11
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• pp.111-116
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• 2017

This paper proposes a data mining approach to predicting stock price direction. Stock market fluctuates due to many factors. Therefore, predicting stock price direction has become an important issue in the field of stock market analysis. However, in literature, there are few studies applying data mining approaches to predicting the stock price direction. To contribute to literature, this paper proposes comparing single classifiers and ensemble classifiers. Single classifiers include logistic regression, decision tree, neural network, and support vector machine. Ensemble classifiers we consider are adaboost, random forest, bagging, stacking, and vote. For the sake of experiments, we garnered dataset from Korea Stock Exchange (KRX) ranging from 2008 to 2015. Data mining experiments using WEKA revealed that random forest, one of ensemble classifiers, shows best results in terms of metrics such as AUC (area under the ROC curve) and accuracy.