• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.334-343
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• 1996

Quality evaluation for food and agricultural products have always been one of the most elusive problems associated with the handling , processing and marketing in a food plant production. In order to detect physical foreign materials in food and agricultural products, non-destructive techniques have been developed for many years. Application of X-ray system to detect physical foreign materials in food and agricultural products could be considered to be a high potential method. Especially , it is impossible to detect internal physical foreign materials by visual inspections. In this study, it was tried to be applied for two different X-ray devices. Soft X-ray system with CdTe sensor and X-ray CT scanner were evaluated for advantage of the detection of non-meltallic foreign materials in food and agricultural products . Though the soft X-ray is not a high energy radiation, it is possible to detect small different density in a material. The CdTe sensor has a high resolution for t e soft X-ray energy region. The density characteristics of foods and foreign material were expressed region. The density characteristics of foods and foreign materials were expressed as a soft X-ray energy spectrum. The energy spectrum was analyzed by a personal computer with a multi-channel analyzer. X-ray CT scanner can provide visual image and analyze by three dimensional information inside food and agricultural products. The X-ray CT scanner using as a medical equipment was used to detect a foreign material. The density characteristics of food and foreign materials in food were tried to be detected by the threshold value on the basis of the CT numbers. The soft X-ray absorption characteristics for acrylin plates and distilled water were obtained and could be found the possibility of detecting a small physical foreign materials such as a plastic wrapping film , a stone and grasshopper in food and agricultural products.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1116-1120
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• 2004

In the nuclear power plant, there are several cylindrical vessels such as reactor vessel, pressuriser and so on. The vessels are usually constructed by welding large rolled plates, forged sections or nozzle pipes together. In order to assure the integrity of the vessel, these welds should be periodically inspected using sensors such as ultrasonic transducer or visual cameras. This inspection is usually conducted under water to minimize exposure to the radioactively contaminated vessel walls. The inspections have been performed by using a conventional inspection machine with a big structural sturdy column, however, it is so huge and heavy that maintenance and handling of the machine are extremely difficult. It requires much effort to transport the system to the site and also requires continuous use of the utility's polar crane to move the manipulator into the building and then onto the vessel. Setup beside the vessel requires a large volume of work preparation area and several shifts to complete. In order to resolve these problems, we have developed an underwater mobile robot guided by the laser pointer, and performed a series of experiments both in the mockup and in the real reactor vessel. This paper introduces our robotic inspection system and the laser guidance of the mobile robot as well as the results of the functional test.

• Corrosion Science and Technology
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• v.18 no.6
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• pp.253-257
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• 2019

A deep learning based real-time painting surface inspection algorithm is proposed herein, designed for developing an autonomous inspection drone. The painting surface inspection is usually conducted manually. However, the manual inspection has a limitation in obtaining accurate data for correct judgement on the surface because of human error and deviation of individual inspection experiences. The best method to replace manual surface inspection is the vision-based inspection method with a camera, using various image processing algorithms. Nevertheless, the visual inspection is difficult to apply to surface inspection due to diverse appearances of material, hue, and lightning effects. To overcome technical limitations, a deep learning-based pattern recognition algorithm is proposed, which is specialized for painting surface inspections. The proposed algorithm functions in real time on the embedded board mounted on an autonomous inspection drone. The inspection results data are stored in the database and used for training the deep learning algorithm to improve performance. The various experiments for pre-inspection of painting processes are performed to verify real-time performance of the proposed deep learning algorithm.

• Smart Structures and Systems
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• v.19 no.2
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• pp.225-236
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• 2017

Railroad bridges in North America are an integral but aging part of the railroad network and are typically only monitored using visual inspections. When quantitative information is required for assessment, railroads often monitor bridges using accelerometers. However without a sensor to directly measure displacements, it is difficult to interpret these results as they relate to bridge performance. Digital Image Correlation (DIC) is a non-contact sensor technology capable of directly measuring the displacement of any visible bridge component. In this research, a railroad bridge was monitored under load using DIC and accelerometers. DIC measurements are directly compared to serviceability limits and it is observed that the bridge is compliant. The accelerometer data is also used to calculate displacements which are compared to the DIC measurements to assess the accuracy of the accelerometer measurements. These measurements compared well for zero-mean lateral data, providing measurement redundancy and validation. The lateral displacements from both the accelerometers and DIC at the supports were then used to determine the source of lateral displacements within the support system.

• Architectural research
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• v.18 no.4
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• pp.185-190
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• 2016

This study aimed to investigate whether protestant religious facilities are maintained appropriately for people and regular inspections are conducted. As a study method, survey and site investigation were conducted. The survey questionnaire aimed to know the perception of users or responsible persons about safety management and current status of safety management systems while the site investigation aimed to inspect structural conditions by a visual inspection such as proper installation of fire protection equipment and whether regular inspection were conducted. It was found, through the inspection of the current safety management status, that the safety management related persons did not know which parts and how much they manage incorrectly, and did not know the follow-up actions in case of accidents. Therefore, it is essentially required to assign a proper person to the facilities for safety management and to have safety consciousness education. Furthermore, although more than 80% of the surveyed subjects responded that they were familiar with the way to use safety management related facilities and overall instructions, the respondent were concerned about the correspondent training for emergent circumstances.

• Smart Structures and Systems
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• v.16 no.5
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• pp.873-889
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• 2015

In civil engineering, probabilistic seismic risk assessment is used to predict the economic damage to a lifeline system of possible future earthquakes. The results are used to plan mitigation measures and to strengthen the structures where necessary. Instead, after an earthquake public authorities need mathematical models that compute: the damage caused by the earthquake to the individual vulnerable components and links, and the global behavior of the lifeline system. In this study, a framework that was developed and used for prediction purpose is modified to assess the consequences of an earthquake in quasi real-time after such earthquake happened. This is possible because nowadays entire seismic regions are instrumented with tight networks of strong motion stations, which provide and broadcast accurate intensity measure maps of the event to the public within minutes. The framework uses the broadcasted map and calculates the damage to the lifeline system and its component in quasi real-time. The results give the authorities the most likely status of the system. This helps emergency personnel to deal with the damage and to prioritize visual inspections and repairs. A highway transportation network is used as a test bed but any lifeline system can be analyzed.

• Journal of The Korean Astronomical Society
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• v.51 no.4
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• pp.73-88
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• 2018

We present a sample of 54 disk galaxies which have well developed extraplanar structures. We selected them using visual inspections from the color images of the Sloan Digital Sky Survey. Since the sizes of the extraplanar structures are comparable to the disks, they are considered as prominent stellar halos rather than large bulges. A single $S{\acute{e}}rsic$ profile fitted to the surface brightness along the minor-axis of the disk shows a luminosity excess in the central regions for the majority of sample galaxies. This central excess is considered to be caused by the central bulge component. The mean $S{\acute{e}}rsic$ index of the single component model is $1.1{\pm}0.9$. A double $S{\acute{e}}rsic$ profile model that employs n = 1 for the inner region, and varying n for the outer region, provides a better fit than the single $S{\acute{e}}rsic$ profile model. For a small fraction of galaxies, a $S{\acute{e}}rsic$ profile fitted with n = 4 for the inner region gives similar results. There is a weak tendency of increasing n with increasing luminosity and central velocity dispersion, but there is no dependence on the local background density.

• Journal of the Korean Society for Advanced Composite Structures
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• v.1 no.1
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• pp.34-45
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• 2010

This paper describes the design, manufacturing process, testing, application, and assessment of capacity-ratings of the first all advanced composites bridge on a public highway system. In order to verify the bridge design prior to the field application, a sub-scale bridge superstructure was built and tested in the laboratory. The field load test results were compared with those of the finite element analysis for the verification of validity. To investigate its in-service performance, field load testing and visual inspections were conducted under an actual service environment. The paper includes the presentation and discussion for advanced composites bridge capacity rating based on the stress modification coefficients obtained from the test results. The test result indicates that the advanced composites bridge has no structural problems and is structurally performing well in-service as expected. Since these composite materials are new to bridge applications, reliable data is not available for their in-service performance. The results may provide a baseline data for future field advanced composites bridge capacity rating assessments and also serve as part of a long-term performance of advanced composites bridge.

• Structural Engineering and Mechanics
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• v.17 no.3_4
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• pp.347-356
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• 2004

In order to extend the lifetime of buildings and civil infrastructure, patch type fibrous composite retrofitting materials are widely used. Retrofitted concrete columns and beams gain stiffness and strength, but lose toughness and show brittle failure. Usually, the cracks in concrete structures are visible to the naked eye and the status of the structure in the life cycle is estimated through visual inspections. After retrofitting of the structure, crack visibility is blocked by retrofitted composite materials. Therefore, structural monitoring after retrofitting is indispensable and self diagnosis method with optical fiber sensors is very useful. In this paper, we try to detect the peel out effect and find the strain difference between the main structure and retrofitting patch material when they separate from each other. In the experiment, two fiber optic Bragg grating sensors are applied to the main concrete structure and the patching material separately at the same position. The sensors show coincident behaviors at the initial loading, but different behaviors after a certain load. The test results show the possibility of optical fiber sensor monitoring of beam structures retrofitted by the composite patches.

• Structural Monitoring and Maintenance
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• v.1 no.4
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• pp.357-369
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• 2014

In the existing bridge management systems, assessment of the structural behavior is based on the results of visual inspections in which corresponding condition states are assigned to individual elements. In this process, limited attention is given to the correlation between bridge elements from structural perspective. Also, the uncertainty of parameters which affect the structural capacity is ignored. A system reliability-based assessment model is potentially an appropriate replacement for the existing procedures. The aim of this research is to evaluate the system reliability of existing conventional Steel-Reinforced bridge decks over time. The developed method utilizes the reliability theory and evaluates the structural safety for such bridges based on their failure mechanisms. System reliability analysis has been applied to simply-supported concrete bridge superstructures designed according to the Canadian Highway Bridge Design Code (CHBDC-S6) and the deterioration pattern is achieved based on the reliability estimates. Finally, the bridge condition index of an old existing bridge in Montreal has been estimated using the developed deterioration pattern. The results obtained from the developed reliability-based deterioration model and from the evaluation done by bridge engineers have been found to be in accordance.