• Journal of the Korean Society for Precision Engineering
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• v.13 no.12
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• pp.30-37
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• 1996

On-line process control equipment for CO$_{2}$ laser cutting is not available for industrial applications. The major part of the industrial laser cutting machines are adjusted off-line by highly educated engineers. The quality inspection of the sample is visual and referred to different quality scales. Due to the lack of automation the potential laser users hesitate to implement the cutting method. The first step toward an automation of the process is the development of a process monitoring system and the research is cincentrated on the area of on-line quality monitoring during CO$_{2}$ laser cutting. The method is based on the detection of the emitted light from the cutting front by photo diode. The developed monitoring system consists of the OP Amplifier, A/D convertor, power supply and PC. The signal from the photo diode has been undertaken from Fourier analysis and statistical analysis with real time. The photograph of striation pattern was taken by metallurgical microscope. As a result, it is possible to predict the striation pattern according to the beam traveling speed.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.555-567
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• 2023

The cracks in the tunnel are currently determined through visual inspections conducted by inspectors based on images acquired using tunnel imaging acquisition systems. This labor-intensive approach, relying on inspectors, has inherent limitations as it is subject to their subjective judgments. Recently research efforts have actively explored the use of deep learning to automatically detect tunnel cracks. However, most studies utilize public datasets or lack sufficient objectivity in the analysis process, making it challenging to apply them effectively in practical operations. In this study, we selected test datasets consisting of images in the same format as those obtained from the actual inspection system to perform an objective evaluation of deep learning models. Additionally, we introduced ensemble techniques to complement the strengths and weaknesses of the deep learning models, thereby improving the accuracy of crack detection. As a result, we achieved high recall rates of 80%, 88%, and 89% for cracks with sizes of 0.2 mm, 0.3 mm, and 0.5 mm, respectively, in the test images. In addition, the crack detection result of deep learning included numerous cracks that the inspector could not find. if cracks are detected with sufficient accuracy in a more objective evaluation by selecting images from other tunnels that were not used in this study, it is judged that deep learning will be able to be introduced to facility safety inspection.

• Journal of Biosystems Engineering
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• v.40 no.2
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• pp.145-152
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• 2015

Purpose: The inability to adequately judge the efficacy of cleaning and sanitation procedures in deli departments is a recognized food safety concern. In a prior study, our research group demonstrated that visual inspection of cleaned produce processing surfaces could be enhanced through the use of a portable fluorescence imaging device that detected residual produce residues. Methods: To explore the feasibility of using fluorescence imaging to similarly detect residual deli residues, spectra of American, Cheddar, Provolone, and Swiss cheeses and of processed chicken, ham, roast beef, and turkey were acquired using a laboratory hyperspectral imaging system. Circular punches of these commodities were placed onto stainless steel and high density polyethylene coupons for imaging. The coupon materials were selected to represent common surfaces found in deli departments. Results: Analysis of hyperspectral fluorescence images showed that cheeses exhibited peaks in the blue-green region and at around 675 nm. Meats exhibited peaks in the blue-green region with one of four ham and one of four chicken brands exhibiting peaks at around 675 nm, presumably due to use of plant-derived additives. When commodities were intermittently imaged over two weeks, locations of spectral peaks were preserved while intensity of peaks at shorter wavelengths increased with time. Conclusion: These results demonstrate that fluorescence imaging techniques have the potential to enhance surface hygiene inspection in deli departments and, given the immediate availability of imaging results, to help optimize routine cleaning procedures.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.12
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• pp.532-541
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• 2016

The objective of this paper is to support accurate pavement condition assessment and decision of proper maintenance method and time by conducting visual inspection and calculating the remaining life of pavement from falling weight deflectometer(FWD) data. Each was implemented in the same long-term performance pavement(LTPP) sections. Visual inspection was executed to measure pavement condition indices such as crack, rutting and international roughness index(IRI) and the Seoul Pavement Index(SPI) was calculated based on these results. The dynamic modulus was back-calculated from the FWD data. The remaining pavement lives were determined from equivalent single axle loading(ESAL) and FWD data. Correlation of maintenance priority by each result value was examined. Consequently, the correlation between remaining life to Crack and Rutting was higher than the other factors or indicesbecause IRI is not related to FWD value and SPI value consists with IRI value and other indices. The R-square value of correlation of FWD with Crack and Rutting was 0.65, which indicated an insufficient correlation. Consequently, when decision of maintenance of method, time, etc. is determined, FWD data have to be considered with Crack and Rutting because of those relations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.59-66
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• 2019

Small bridges carry out only general inspections based on visual inspection. The Bridges with more than 30 years of public use need to be decided on whether or not they will be reconstruction according to aging. However, there are some situations that need to be determined only by appearance condition, which is insufficient in terms of safety maintenance. In this paper, the condition evaluation and the load carrying capacity evaluation were carried out for aged small bridges. A comparison of the evaluation results was conducted to examine the appropriateness of the maintenance related to the decision making of the reconstruction. As a result of reviewing, two of the bridges showed that there are no abnormality in the safety of the state evaluation, but the load capacity were insufficient. Thus evaluation the safety and performing the reconstruction decision of aged small bridges by visual inspection alone with may cause problems. Therefore, it is necessary to carry out additional research on the ambient measurement and load carrying capacity evaluation for the maintenance of the bridges, and to supplement it through application of the bridge management system.

• Journal of the Korean Society of Hazard Mitigation
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• v.5 no.4 s.19
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• pp.9-15
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• 2005

This research developed the RMIS(Risk Management Information System) which focus on works of risk management fields required of apply of a space information, and focus on the DB to establish and apply the space information efficiently with research scope on the LPG refueling station in city. On the basis of the RMIS, this research provides the baseline to lead on an efficiency of safety inspection of LPG refueling station, advance risk assessment, and efficient making decision of an accident correspondence assessment with interlocking the GIS representing risk through the automation of a quantitative risk assessment standardize requirement to control at real-time. The RMIS development process is as follows. firstly, Relational Database(RDB) was developed by using fundamental data both On-site and Off-site relating data as peforming risk assessment on the LPG refueling station in city. Second, the risk management integral database system was developed to monitor and control the risk efficiently for user with using the Visual Basic Program. Third, through interlocking the risk management integral database system and the GIS(Falcon-map) was suggested the decision making method. Represented results through out the RMIS program development are as follows. Firstly, the RMIS was established the mutual information to advance management the risk efficiently for user and inspector with using the risk management data. Second, as this study managed risk for on-site and off-site separately and considered effect for inside and outside of facility, constructed the basis on safety management which can respond to major accident. Third, it was composed the baseline to making decision that on the basis of user interface.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.3
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• pp.644-653
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• 1998

In resistance spot weld, the assurance of weld quality has been a long-standing problem. Since the weld nuggets if resustance spot welding form between the workpieces, visual detection of defects in usually impossible. Welding quality of resistance spot welding can be verified by non destructive and destructive inspections such as X-Ray inspection and testing of weld strength. But these tests, in addition to being time-consuming and costly, can entail risks due to sampling basis. The purpose of this study is the development of the monitoring system based on fuzzy inference, aimed at diagonosis of quality in resistance spot welding. The fuzzy inference system consists of fuzzy input variables, fuzzy membership functions and fuzzy rules. For inferring the welding quality(strength), the experimental data of the spot welding were acquired in various welding conditions with the monitoring system designed. Some fuzzy input variables-maximum, slop and difference values of electrode movement signals-were extracted from the experimental data. It was confirmed that the fuzzy inference values of strength have a .${\pm}$5% error in comparison with actual values for the selected welding conditions(9-10.5KA, 10-14 cycle, 250-300 $kg_f$). This monitoring system can be useful in improving the quality assurance and reliability of the resistance spot welding process.

• Journal of Biosystems Engineering
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• v.31 no.6 s.119
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• pp.514-523
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• 2006

Production of green pepper has been increased due to customer's preference and a projected ten-year boom in the industry in Korea. This study was carried out to develop an automatic grading and sorting system for green pepper using machine vision. The system consisted of a feeding mechanism, segregation section, an image inspection chamber, image processing section, system control section, grading section, and discharging section. Green peppers were separated and transported using a bowl feeder with a vibrator and a belt conveyor, respectively. Images were taken using color CCD cameras and a color frame grabber. An on-line grading algorithm was developed using Visual C/C++. The green peppers could be graded into four classes by activating air nozzles located at the discharging section. Length and curvature of each green pepper were measured while removing a stem of it. The first derivative of thickness profile was used to remove a stem area of segmented image of the pepper. While pepper is moving at 0.45 m/s, the accuracy of grading sorting for large, medium and small pepper are 86.0%, 81.3% and 90.6% respectively. Sorting performance was 121 kg/hour, and about five times better than manual sorting. The developed system was also economically feasible to grade and sort green peppers showing the cost about 40% lower than that of manual operations.

• Korean Journal of Oriental Medicine
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• v.14 no.3
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• pp.89-95
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• 2008

A tongue shows physiological and clinicopathological changes of inner organs. Visual inspection of a tongue is not only convenient but also non-invasive. To develop an automat ic tongue diagnosis system for an objective and standardized diagnosis, the separation of the tongue are a from a facial image and the detection of coatings, spots and cracks are inevitable but difficult since the colors of a tongue, lips, and skin in a mouth as well as those of tongue furs and body are similar. The propose d method includes preprocessing with down-sampling and edge enhancement, over-segmentation, detecting positions with a local minimum over shading from the structure of a tongue, and correcting local minima or detecting edge with color difference. The proposed method produces the region of a segmented tongue, and then decomposes the color components of the region into hue, saturation and brightness, resulting in classifying the regions of tongue furs(coatings) into kinds of coatings and substance and segmenting them. Spots are detected by using local maxima and the variation of saturation, and cracks are searched by using local minima and the directivity of dark areas in brightness. The results illustrate the segmented region with effective information, excluding a non-tongue region and also give us accurate discrimination of coatings and the precise detection of spots and cracks. It can be used to make an objective and standardized diagnosis for an u-Healthcare system as well as a home care system.

• The Korean Journal of Community Living Science
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• v.24 no.2
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• pp.251-258
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• 2013

Korean oil and honey Yukwa has been paid attention as formal cake for traditional national seasons' holiday and religious service. Quality of Yukwa, however, has been maintained arbitrarily by each Yukwa manufacturer. Since even same Yukwa had severe differences in size, weight, and pattern, it has given the negative effect to the consumer. Yukwa industries need to setup the quantitative quality specifications instead of qualitative ones to maintain the uniformity of Yukwa quality. Efficient and economical inspection and process control system should be developed. In developing quality standards of Yukwa, features which can measure quality quantitatively in real time should be properly chosen. Existing quality features such as acidity, oxidization, hardness, viscosity, and texture were measured by the chemical or physical base destructive methods. Many research and developments have been performed in investigating and analyzing chemical transition states of those quality features as environment or storage condition changes. Most methods, however, require either off-line or complex treatment or time consuming process of analysis in evaluating quality features. Consumer, however, selects products mostly based on the external features such as shape, size, and color. Therefore, critical visual quality features should be chosen and the efficient real time measurement system must be developed. In this paper, computer image acquisition and processing system were developed and software modules were developed to extract the quantitative data of those features in real-time. Computer image processing system will promote in maintaining uniform quality of Yukwa and establishing quality standards of Yukwa.