• Journal of the Korean Society for Nondestructive Testing
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• v.5 no.2
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• pp.53-57
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• 1986

이상적인 검사는 합부판정 기준보다 큰 결함을 100%검출, 불합격시키고 그보다 작은 결함은 100% 합격시킬 수 있으나 현실적으로 이는 불가능하고 검사의 본질적인 불확실성으로 인해 때로는 합격되어야 할 결함이 불합격으로 처리되거나 (TYPE 1 ERROR라 칭함) 불합격되어야 할 결함이 합격으로 처리되기도 한다. (TYPE 2 ERROR) TYPE 1 ERROR 및 TYPE 2 ERROR를 동시에 줄이기 위해서는 검사의 불확실성을 제거하여야 하며 주어진 합부판정 기준과 검사불확실성하에서 검사를 둘러싼 총경비를 최소화시키기 위하여는 TYPE 1 ERROR와 TYPE 2 ERROR의 확률 및 그로 인한 예상 경비를 관련시켜야 한다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1380-1383
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• 2004

The scanning type XY stage is frequently used these days as precision positioning system in equipment for semiconductor or display element. It is requested higher velocity and more precise accuracy for higher productivity and measuring performance. The position accuracy of general stage is primarily affected by the geometric errors caused by parasitic motion of stage, misalignments such as perpendicular error, and thermal expansion of structure. In the case of scanning type stage, H type frame is usually used as base stage which is driven by two actuators such as linear motor. In the point view of scanning process, the stage is used in moving motion. Therefore, dynamic variation is added as significant position error source with other parasitic motion error. Because the scanning axis is driven by two actuators with two position detectors, 2 dimensional position errors have different characteristic compared to general tacked type XY stage. In this study 2D position error of scanning stage is analyzed by 1D heterodyne interferometer calibrator, which can measure 1D linear position error, straightness error, yaw error and pitch error, and perpendicular error. The 2D position error is evaluated by diagonal measurement (ISO230-6). The yaw error and perpendicular error are compensated on the base stage of scanning axis. And, the horizontal straightness error is compensated by cross axis compensation. And, dynamic motion error in scanning motion is analyzed.

• Nuclear Engineering and Technology
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• v.23 no.2
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• pp.174-182
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• 1991

Effects of human error relevant to the periodic test are incorporated in the evaluations of the unavailability and optimal test interval of a safety system. Two types of possible human error with respect to the test and maintenance are considered. One is the possibility that a good safety system is inadvertently left in a bad state after test（Type A human error) and the other is the possibility that a bad safety system is undetected upon the test（Type B human error). An event tree model is developed for the steady-state unavailability of a safety system in order to determine the effects of human errors on the system unavailability and the optimal test interval. A reliability analysis of the Safety Injection System (SIS) was peformed to evaluate the effects of human error on the SIS unavailability. Results of various sensitivity analyses show that ; (1) the steady-state unavailability of the safety system increases as the probabilities of both types of human error increase and it is far more sensitive to Type A human error, (2) the optimal test interval increases slightly as the probability of Type A human error increases but it decreases as the probability of Type B human error increases, and (3) provided that the test interval of the safety injction pump is kept unchanged, the unavailability of SIS increases significantly as the probability of Type A human error increases but slightly as the probability of Type B human error increases. Therefore, to obtain the realistic result of reliability analysis, one should take shorter test interval (not optimal test interval) so that the unavailability of SIS can be maintained at the same level irrespective of human error. Since Type A human error during test & maintenance influeces greatly on the system unavailability, special efforts to reduce the possibility of Type A human error are essential in the course of test & maintenance.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.5
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• pp.502-508
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• 2012

Heliostat, as a concentrator to reflect the incident solar energy to the receiver, is the most important system in the tower-type solar thermal power plant since it determines the efficiency and ultimately the overall performance of solar thermal power plant. Thus, a good sun tracking ability as well as a good optical property of it are required. Heliostat sun tracking system uses usually an open loop control system. Thus the sun tracking error caused by heliostat's geometrical error, optical error and computational error cannot be compensated. Recently use of sun tracking error model to compensate the sun tracking error has been proposed, where the error model is obtained from the measured ones. This work is a development of heliostat sun tracking error measurement and compensation method using BCS (Beam Characterization System). We first developed an image processing system to measure the sun tracking error optically. Then the measured error is modeled in linear polynomial form and neural network form trained by the extended Kalman filter respectively. Finally error models are used to compensate the sun tracking error. We also developed the necessary image processing algorithms so that the heliostat optical properties such as maximum heat flux intensity, heat flux distribution and total reflected heat energy could be analyzed. Experimentally obtained data shows that the heliostat sun tracking accuracy could be dramatically improved using either linear polynomial type error model or neural network type error model. Neural network type error model is somewhat better in improving the sun tracking performance. Nevertheless, since the difference between two error models in compensation of sun tracking error is small, a linear error model is preferred in actual implementation due to its simplicity.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.183-186
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• 2007

We introduction some properties for fuzzy power function of performance of a test. First we define fuzzy type I error and type II error for the probability of the two types of error. And we show that an fuzzy error probability of one kind can only be reduced at cost of increasing the other fuzzy error probability.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.805-808
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• 2005

This paper is a study on an optical bench satisfying stiffness and thermal pointing error requirements for LEO earth observation satellite. According to shape and stiffness requirements, optical bench type 1 is designed. Because type 1 does not satisfy the thermal pointing error requirement, an optical bench type 2 is suggested. Although the type 2 has better results than type 1, it still does not meet the thermal pointing error requirement. Using the results of optical bench type 1&2, the optical bench type 3 is finally designed, which satisfies both the stiffness and thermal pointing error requirements.

• Journal of the Korean Society of Safety
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• v.22 no.4
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• pp.66-71
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• 2007

Human error is one of the major contributors to the railway accidents or incidents. In order to develop an effective countermeasure to remove or reduce human errors, a systematic analysis should be preferentially performed to identify their causes, characteristics, and types of human error induced in accidents or incidents. This paper introduces a case study for human error analysis of the railway accidents and incidents. For the case study, more than 1,000 domestic railway accidents or incidents that happened during the year of 2004 have been investigated and a detailed error analysis was performed on the selected 90 cases, which were obviously caused by human error. This paper presents a classification structure for human error analysis, and summarizes the analysis results such as causes of the events, error modes and types, related worker, and task type.

• 한국데이터정보과학회:학술대회논문집
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• 2004.10a
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• pp.17-23
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• 2004

At the conclusion from the hypothesis testing, there is a possibility of making Type I error and Type II error. The purpose of this article is to use this program in statistics teaching through developing the program for studying on the concept about these two errors, two kinds of the probability of errors by the variation of rejection region, two kinds of the probability of errors by the variation of sample size, the relations of the probability $\alpha$ and $\beta$ by these two errors, and power function, power curve.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.177-177
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• 2000

In this paper, we propose a two-input two-output fuzzy controller to improve the performance of transient response and to eliminate the steady state error. The outputs of this controller are the control input calculated by position-type fuzzy controller and the accumulated error scaling factor. Here, the accumulated error scaling factor is adjusted on-line by fuzzy rules according to the current trend of the controlled process. To show the usefulness of the proposed controller, it is applied to several systems that are difficult to get satisfactory response by conventional PD controllers or PI controllers.

• Proceedings of the Safety Management and Science Conference
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• 2011.11a
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• pp.123-133
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• 2011

This paper reviewed the relationship between job stress and human error, and the moderating effect of age and maintenance type on the relationship between job stress and human error in maintenance personnel. Based on the responses from 450 maintenance personnels, the results of multiple regression analysis showed that physiological and psychological stress responses have positively related with human error. In moderating effect test, age appeared to impact on the relationship between physiological/behavioral stress and human error.