• Journal of the Korean Society for Precision Engineering
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• v.32 no.12
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• pp.1039-1047
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• 2015

Contact type sensors (e.g., displacement sensor and strain gauge) were typically used to evaluate the safety and mechanical properties in machines and construction. However, those contact type sensors have been constrained because of measurement problems such as surface roughness, temperature, humidity, and shape. The Digital Image Correlation (DIC) measurement system is a vision measurement system. This measurement system uses the taken image using a CCD camera and calculates the image correlation between the reference image and the deformed image under external force to measure the displacement and strain rates. In this paper, we discuss methods to improve the measurement precision of the digital image correlation measurement system. A tensile test was conducted to compare the precision improvement effects, by using the universal test machine and the DIC measurement system, with the use of subpixel algorithms, i.e., the Coarse Fine Search (CFS) algorithm and the Peak Finding (PF) algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.3
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• pp.274-279
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• 2008

Roll to roll (R2R) manufacturing process, also known as 'web processing', has been tried for producing electronic devices on a flexible plastic or metal foil. To increase the performance and productivity the R2R process, effective control and on-line supervision for web quality becomes very important. Wrinkle is one of the defects, which is incurred due to compressive stresses. A system for on-line measurement of wrinkle is developed using area scan camera and machine vision laser. The 2D image, obtained by area scan camera, is produced by Gaussian regression method to characterize the wrinkle on a transparent web. The experiment proves that 0.3mm wrinkle height can be measured successfully with 74fps.

• Journal of Mechanical Science and Technology
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• v.18 no.8
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• pp.1349-1357
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• 2004

Computer-Aided Inspection Planning (CAIP) is the integration bridge between CAD/CAM and Computer Aided Inspection (CAI). A CAIP system for On-Machine Measurement (OMM) is proposed to inspect the complicated mechanical parts efficiently during machining or after machining. The inspection planning consists of Global Inspection Planning (GIP) and Local Inspection Planning (LIP). In the GIP, the system creates the optimal inspection sequence of the features in a part by analyzing the various feature information such as the relationship of the features, Probe Approach Directions (PAD), etc. Feature groups are formed for effective planning, and special feature groups are determined for sequencing. The integrated process and inspection plan is generated based on the sequences of the feature groups and the features in a feature group. A series of heuristic rules are developed to accomplish it. In the LIP of Part II, the system generates inspection parameters. The integrated inspection planning is able to determine optimum manufacturing sequence for inspection and machining processes. Finally, the results are simulated and analyzed to verify the effectiveness of the proposed CAIP.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.4
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• pp.92-97
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• 2006

This paper presents an integrated machining error compensation method based on PNN(Polynomial Neural Network) approach and inspection database of OMM(On-Machine-Measurement) system. To efficiently analyze the machining errors, two machining error parameters are defined and modeled using the PNN approach, which is used to determine machining errors for the considered cutting conditions. Experiments are carried out to validate the approaches proposed in this paper. In result, the proposed methods can be effectively implemented in a real machining situation, producing much fewer errors.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.12 s.255
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• pp.1649-1657
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• 2006

Fizeau interferometer is well known optical instrument for measuring the lens profile accurately. The object of this study is focused on the design and optical measuring techniques for large optical components, such as a reflection mirror for astronomical purpose. Measuring of large optical lens, the object could not be moved as small one but the measuring instrument must be moved for the alignment, because of the geometric conditions and the accuracy of the stage. Therefore, a five axis stage is designed to align the Interferometer instead of the measuring object. This instrument will be used for an on machine measuring system in polishing machine for large optical lens.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.6
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• pp.68-73
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• 2009

One of the traditional optical methods to monitor a tool is a CCD sensor-based vision system which captures an aspect of the tool in real time. In the case using the CCD sensor, specific lens-modules are necessary to monitor the tool with higher resolution than its pixel size, and a microprocessor is required to attain desired data from captured images. Thus theses additional devices make the entire measurement system complex. Another method is to use a pair of an optical source and a detector per measuring axis. Since the method is based on the intensity modulation, the structure of the measurement system is simper than the CCD sensor-based vision system. However, in the case measuring the three dimensional position of the tool, it is difficult to apply to micro machine-tools because there may not be space to integrate three pairs of an optical source and a detector. In this paper, in order to develop a tool-origin measurement system which is employed in micro machine-tools, the improved method to measure a tool origin in x, y and z axes is introduced. The method is based on the intensity modulation and employs one pair of an optical source radiating divergent beams and a quadrant photodiode to detect a three dimensional position of the tool. This paper presents the measurement models of the proposed tool-origin sensor. The models were verified experimentally The verification results show that the proposed method is possible and the induced models are available for design.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.1
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• pp.97-103
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• 2013

This study proposes a path generation technique for simultaneous five-axis driving for ball bar measurement, which is equivalent to cone frustum machining as mentioned in the NAS979 standard. The technique is generalized for a 3D circular path, and it is applicable to all machine tools regardless of their structural configurations. A mathematical machine input model that consists of a five-axis machine tool, ball-bar measurement and conical path information as inputs is presented for easy NC code generation, simulation for various test conditions, and a measurement test. The movement range of rotary axes, which depends on various conditions, is mathematically analyzed based on the proposed conical path model. Moreover, the effect of the movement range on various conditions (apex angle and inclination angle, ball bar tilting acceptance angle, offset position of workpiece ball, etc.) is analyzed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.748-754
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• 1994

This paper deals with a geometric error simulator, measurement and inspection of workpiece errors on the machine tools, and identification and compensation methodology of thermal errors in machining centers. In order to raise the machining accuracy of workpieces a measurement and inspection system on the machine tool is developed. By using MPPGT module Manual and CNC type CMMs are realized on the machining centers. To compensate for geometric and thermal deformation errors of machining centers, a real time and an off line geometric adaptive control system were developed on the machining centers. A vertical and a horizontal machining center equipped with FANUC 0MC were used for experiments. Performance of the systems were confirmed with a large amount of experiment.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1220-1224
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• 2003

In this paper, we measured the radiation dose of a fuel handling machine of the CANDU type Wolsong nuclear reactor directly during operation, in spite of the high radiation level. In this paper we will describe the sensor development, measurement techniques, and results of our study. For this study, we used specially developed semiconductor sensors and matching dosimetry techniques for the mixed radiation field. MOSFET dosimeters with a thin oxide, that are tuned to a high dose, were used to measure the ionizing radiation dose. Silicon diode dosimeters with an optimum area to thickness ratio were used for the radiation damage measurements. The sensors are able to distinguish neutrons from gamma/X-rays. To measure the radiation dose, electronic sensor modules were installed on two locations of the fuel handling machine. The measurements were performed throughout one reactor maintenance cycle. The resultant annual cumulative dose of gamma/X-rays on the two spots of the fuel handling machine were 18.47 Mrad and 76.50 Mrad, and those of the neutrons were 17.51 krad and 60.67 krad. The measured radiation level is high enough to degrade certain cable insulation materials that may result in electrical insulation failure.

• International journal of advanced smart convergence
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• v.12 no.2
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• pp.47-55
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• 2023

The automotive industry is undergoing a paradigm shift due to the convergence of IT and rapid digital transformation. Various components, including embedded structures and systems with complex architectures that incorporate IC semiconductors, are being integrated and modularized. As a result, there has been a significant increase in vehicle defects, raising expectations for the quality of automotive parts. As more and more data is being accumulated, there is an active effort to go beyond traditional reliability analysis methods and apply machine learning models based on the accumulated big data. However, there are still not many cases where machine learning is used in product development to identify factors of defects in performance and durability of products and incorporate feedback into the design to improve product quality. In this paper, we applied a prediction algorithm to the defects of automotive door devices equipped with automatic responsive sensors, which are commonly installed in recent electric and hydrogen vehicles. To do so, we selected test items, built a measurement emulation system for data acquisition, and conducted comparative evaluations by applying different machine learning algorithms to the measured data. The results in terms of R² score were as follows: Ordinary multiple regression 0.96, Ridge regression 0.95, Lasso regression 0.89, Elastic regression 0.91.