• Journal of Korean Society for Quality Management
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• v.22 no.4
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• pp.28-39
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• 1994

This study is concerned with determination of an optimal target value in a filling process. Complete inspection procedures are widely used to improve outgoing quality of products. In many cases, however, it may be impossible or noneconomical to measure the quality characteristic, performance variable, directly. In such cases, it is a common practice to select an easily measurable variable which is highly correlated with the performance variable and perform screening products for the variable. This study proposes a model to determine the target value and the inspection rule based on the screening variable. This, study deals with the cases in which rejected products would be scrapped and sold at a reduced price in secondary markets.

• Journal of the Korean Data and Information Science Society
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• v.15 no.4
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• pp.867-877
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• 2004

The sequential sampling inspection method is an extension of the multiple-sampling methods, and its theory is based on the sequential probability ratio test (SPRT) of Wald. In this paper, the characteristics of SPRT for testing the number of defects are approximated by using the estimated excess over the boundaries. The use of the estimated excess shows good performances in estimating the operating characteristic function and the average sample number of SPRT compared to the method by neglecting the excess. It also makes it possible to determine the boundary values which satisfy the desired error probabilities.

• Journal of Biosystems Engineering
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• v.23 no.6
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• pp.621-628
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• 1998

In order to develop an inspection algorithm for an automatic eggshell inspection system, acoustic impulse response with neural network method was studied. An improved error backpropagation algorithm was selected as a loaming rule of neural network, and three layer network was chosen for the neural network architecture. Acoustic signals in time domain and theirs power spectrum were studied as the input to the neural network. The classification feasibility and success rate were investigated in terms of statistical analysis and neural network approach. As a result, the success rate was 95% with the statistical model having five independent variables. Among the neural network models studied, the power spectrum of acoustic signal as the input with 64 input neurons and the two impact data showed the success rate of 95.5% which was slightly higher than of statistical analysis.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.389-390
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• 2006

The goal of this paper is automation of a remocon inspection process using machine vision system. This system prevents error that is occurred by physical and spirit condition of human. Also this system has been developed to raise the reliability of remocon inspection. This system has been developed only using PC, CCD Camera and Visual C++ for universal workplaces. The performance of this system is an accuracy improvement of $2{\sim}3[%]$ and a processing time reduction of about 100[ms] against existing pattern matching method.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.5
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• pp.548-554
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• 2009

We propose an automatic inspection system for hologram with multiple patterns. The system hardware consists of illuminations, camera, and vision processor. Multiple illuminations using LEDs are arranged in different directions to acquire each image of patterns. The system software consists of pre-processing, pattern generation, and pattern matching. The acquired images of input hologram are compared with their reference patterns by developed matching algorithm. To compensate for the positioning error of input hologram, reference patterns of hologram for different position should be generated in on-line. We apply a frequency transformation based CGH(computer-generated hologram) method to generate reference images. For the fast pattern matching, we also apply the matching method in the frequency domain. Experimental results for hologram of Korean currency are then presented to verify the usefulness of proposed system.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.3
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• pp.207-211
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• 2010

In this paper, the fluid AID(acoustic inspection device) was developed to measure SOS(speed of sound) since fluids used in most of industrial fields have different properties and its equipment is highly expensive. From AID developed, it is intended to get potentially the capability to distinguish the kind of fluid using the measurement by the SOS at various fields. In order to measure the sound speed of specific fluids, the measurement system and ultrasonic sensors are composed. The fluid used in the experimental work are soybean oil, glycerin, diesel oil and the error of time difference due to the container wall is extracted for preliminary experiment. As results, the variations of sound speed according to the temperature change of target fluid were analyzed and the polynomial equations were proposed.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.05a
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• pp.270-273
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• 2003

The strain measurement of the panel in the sheet metal forming is essential work which provides experimental data needed to die design, process design, and product inspection. To measure efficiently the complex geometry strain, the 3-dimensional automative strain measurement system, which has high accuracy in theory, but has some 3∼5% errors in practice, is often used. The object of this study is to develop the error compensation technology to eliminate the strain, errors resulted when formed panels are measured using an automated strain measurement system. To achieve the study object, the position error calibration method correcting coordinates of the grid node recognized by a camera using error functions is suggested. Then the position errors were found by calculating the difference in the position of the cube node between real coordinates and measured coordinates in toms of node coordinates and the error calibration equations were derived by regressing the position errors. In order to show the validation of the suggested position error calibration method, finite element analysis and current calibration method was performed for the initial-blankformed.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.4
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• pp.77-83
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• 2016

Recently, interests for maintenance of transmission tower are increasing to extend life of structures and reduce maintenance cost. However, existing classical diagnosis method of corrosion deteriorated degree on the transmission tower steel members, visual inspection, has a problem that error often due to difference of inspector's individual knowledge and experience. In order to solve the problem, this study carried out to develop the corrosion deterioration inspection tool for transmission tower steel members. This tool is composed of camera equipment and computer-aided diagnosis system. We standardized the photographing method by camera equipment to obtain suitable pictures for image processing. Diagnosis system was designed to evaluate automatically degree of corrosion deterioration for member of transmission tower on the basis of the RGB color image processing techniques. It is anticipated that developed the corrosion deterioration inspection tool will be very helpful in decision of optimal maintenance time for transmission tower corrosion.

• Korean Journal of Construction Engineering and Management
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• v.24 no.4
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• pp.52-59
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• 2023

Flatness inspection of PC elements is normally conducted manually by inspectors at manufacturing sites. However, the manual inspection is error-prone and subjective, so it is necessary to develop a robust and efficient flatness measurement method. Recently, a few studies of laser scanner-based flatness inspection have been conducted. However, little attention on field applicability in terms of accuracy, time and cost has been paid. To tackle the limitation, this study aims to compare three sensing method including floor profiler, terrestrial laser scanner and total station for flatness inspection of PC elements. A series of experiments on two full-scale PC slabs were conducted and the results show that the laser scanning method is the most suitable for the PC elements flatness inspection in the aspects of accuracy, time and cost.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.376-381
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• 2001

This paper presents a methodology of machining error compensation by using Artificial Neural Network(ANN) model based on the inspection database of On-Machine-Measurement(OMM) system. First, the geometric errors of the machining center and the probing errors are significantly reduced through compensation processes. Then, we acquire machining error distributions from a specimen workpiece. In order to efficiently analyze the machining errors, we define two characteristic machining error parameters. These can be modeled by using an ANN model, which allows us to determine the machining errors in the domain of considered cutting conditions. Based on this ANN model, we try to correct the tool path in order to effectively reduce the errors by using an iterative algorithm. The iterative algorithm allows us to integrate changes of the cutting conditions according to the corrected tool path. Experimentation is carried out in order to validate the approaches proposed in this paper.