• Proceedings of the KIEE Conference
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• 2003.10b
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• pp.203-205
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• 2003

This paper is proposed a newly developed approach to identify the mechanical speed of an induction motor based on artificial neural networks technique. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.10
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• pp.690-696
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• 2004

This paper is proposed a hybrid intelligent controller based on the vector controlled surface permanent magnet synchronous motor(SPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of SPMSM using neural network-fuzzy(NNF) control and speed estimation using artificial neural network(ANN) Controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.8
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• pp.545-550
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• 2004

This paper is proposed a fuzzy neural network controller based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed estimation and control of speed of induction motor using ANN Controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

• Journal of Power Electronics
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• v.17 no.4
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• pp.1027-1036
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• 2017

The brushless doubly-fed induction generator (BDFIG) is a new type of dual stator winding induction generator. In such a generator, both the power winding (PW) and the control winding (CW) are housed in the stator. This paper presents the performance characteristics of a stand-alone BDFIG operation system. A new T-type steady-state model of a BDFIG is proposed. This model is more suitable for the performance analysis of stand-alone BDFIGs than the conventional Π-type steady-state model and the simplified inner core steady-state model. The characteristics of the power flow and CW current are analyzed by detailed mathematical derivations on the basis of the proposed T-type steady-state model. The analysis results are verified by experiments, which are carried out on a prototype BDFIG. The results of the performance analysis contribute to simplifying the control circuit, improving the control performance, and selecting an appropriate BDFIG for actual industrial applications.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.3
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• pp.282-289
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• 2005

This paper proposes a fuzzy neural network controller based on the vector control for interior permanent magnet synchronous motor(IPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability This paper does not oかy presents speed control of IPMSM using neuro-fuzzy control(NFC) but also speed estimation using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. Thus, it is presented the theoretical analysis as well as the analysis results to verify the effectiveness of the proposed method in this paper.

• Journal of KIBIM
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• v.9 no.3
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• pp.1-7
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• 2019

Digital twin technology has been actively developed to monitor and assess the current state of actual structures. The digital twin changes the traditional observation method performed in the field to the real-time observation and detection system using virtual online model. Thus, this study designed a digital twin model for a beam and examined the feasibility of the digital twin for bridges. To reflect the current state of the bridge, model updating was performed according to the field test data to construct an analysis model. Based on the constructed bridge analysis model, the relationship between strain and displacement was used to represent a virtual model that behaves in the same way as the actual structure. The strain and displacement relationship was expressed as a matrix derived using an approximate analytical theory. Then, displacements can be obtained using the measured data obtained from strain sensors installed on the bridge. The coordinates of the obtained displacements are used to construct a virtual digital model for the bridge. For verification, a beam was fabricated and tested to evaluate the digital twin model constructed in this study. The displacements obtained from the strain and displacement relationship agrees well with the actual displacements of the beam. In addition, the displacements obtained from the virtual model was visualized at the locations of the strain sensor.

• JSTS:Journal of Semiconductor Technology and Science
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• v.6 no.4
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• pp.299-312
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• 2006

This paper presents the results of a novel test structure for process control monitor for uncooled IR detector technology of microbolometer arrays. The proposed test structure is based on resistive network configuration. The theoretical model for resistance of this network has been developed using 'Compensation' and 'Superposition' network theorems. The theoretical results of proposed resistive network have been verified by wired hardware testing as well as using an actual 16x16 networked bolometer array. The proposed structure uses simple two-level metal process and is easy to integrate with standard CMOS process line. The proposed structure can imitate the performance of actual fabricated version of area array closely and it uses only 32 pins instead of 512 using conventional method for a $16{\times}16$ array. Further, it has been demonstrated that the defective or faulty elements can be identified vividly using extraction matrix, whose values are quite similar(within the error of 0.1%), which verifies the algorithm in small variation case(${\sim}1%$ variation). For example, an element, intentionally damaged electrically, has been shown to have the difference magnitude much higher than rest of the elements(1.45 a.u. as compared to ${\sim}$ 0.25 a.u. of others), confirming that it is defective. Further, for the devices having non-uniformity ${\leq}$ 10%, both the actual non-uniformity and faults are predicted well. Finally, using our analysis, we have been able to grade(pass or fail) 60 actual devices based on quantitative estimation of non-uniformity ranging from ＜ 5% to ＞ 20%. Additionally, we have been able to identify the number of bad elements ranging from 0 to ＞ 15 in above devices.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.664-667
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• 1997

For higher component density per chip, it is necessary to identify and control the semiconductor manufacturing process more stringently. Recently, neural networks have been identified as one of the most promising techniques for modeling and control of complicated processes such as plasma etching process. Since wafer states after each run using identical recipe may differ from each other, conventional neural network models utilizing input factors only cannot represent the actual state of process and equipment. In this paper, in addition to the input factors of the recipe, real-time tool data are utilized for modeling of 64M DRAM s-poly plasma etching process to reflect the actual state of process and equipment. For real-time tool data, we collect optical emission spectroscopy (OES) data. Through principal component analysis (PCA), we extract principal components from entire OES data. And then these principal components are included to input parameters of neural network model. Finally neural network model is trained using feed forward error back propagation (FFEBP) algorithm. As a results, simulation results exhibit good wafer state prediction capability after plasma etching process.

• Journal of the Korean Society of Safety
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• v.32 no.2
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• pp.27-33
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• 2017

This study is intended to identify issues on the basis of investigating the actual state of laboratory environment and outlet circuit, and derive end states by expressing sequences from the initiating event of disaster to accident in leakage current, poor contact and overload through ETA(event tree analysis). To this end, this study investigated the actual state of electric equipment of laboratory at universities in all parts of country. And it is shown that most of them are failure in electric work and user negligence in the investigation of actual state. It is found that there is earth fault and defect in wire diameter in the failure of electric work and the problem of partial disconnection due to wire bundling and poor contact in user negligence. Outlet-related component, failure rate and initiating events are composed of a total of 41 initiating events, i.e., 30 internal initiating events and 11 external initiating events. And end states are composed of a total of 15 parts, i.e., 3 electric power parts and 12 safety parts. Earthing class 3 is the most important safety device against leakage current (initiating event). And in case of poor contact, it is necessary for manager to check thoroughly because there is no safety device. In case of overload/overcurrent, when high-capacity equipment is connected, a molded case circuit breaker, safety device, worked. However, in most cases, it is verified that this doesn't work. This study can be utilized as electric equipment safety guide for laboratory safety manager and managers.

• Journal of Korean Society of Rural Planning
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• v.19 no.4
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• pp.191-202
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• 2013

This study aims at providing the basic information required for policies on return to countryside for farming or else, through analysing the actual state of settlement and the community of people returning to rural areas. The comparative analysis of people returning toward general village and sub-urban residential complex in rural has been done to figure out the settlement environment. And the status analysis targeting the people returning to rural areas and original residents who live in general village have been done to figure out the actual state of the community. As a result, people returning toward sub-urban residential complex in rural moved for something else, while people returning toward general village in rural moved with the purpose of farming. Like this, the aims of moving into rural areas show difference. There is little conflict between people returning to rural areas and original residents, but some people have an intention to move the other place due to the conflict with original residents. So the community revitalization is needed for the active responses and suitable adaptation of them. On the basis of this study, policy tasks for return to countryside for farming or else were suggested as follows; 1) It is necessary to formulate each policy on return for farming and something else to rural areas discriminatively. 2) The economic support for a stable settlement of people returning to rural areas and the programs activating community with original residents are required. The discussion about the new community formation is needed to respond to the increase of people returning to rural areas.