• Agricultural and Biosystems Engineering
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• v.4 no.1
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• pp.1-7
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• 2003

Internal defects such as browning of the flesh and blackening and rot of the ovary of pear can be easily developed because of the inadequate environmental conditions during the storage and distribution of fruit. The quality assurance system for the agricultural product is to be settled in Korea. All defected agricultural products should be excluded prior to the distribution to enhance the commercial values. However, early stage on-line defect detection of agricultural product is very difficult and even more difficult in a case of the internal defects. The goal of this research is to develop a system that can detect and classify internal defects of agricultural produce on-line using VIS/NIR transmittance spectroscopy. And Shingo pear, which is one of the famous species of Korean pear, was used for the experiment. Soft independence modeling of class analogy (SIMCA) algorithm was employed to analyze the transmittance spectroscopic data qualitatively. On-line classification system was constructed and classification model was developed and validated. As a result, the correct classification rate (CCR) using the developed classification model was 96.1 ％.

• Smart Structures and Systems
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• v.9 no.5
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• pp.461-472
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• 2012

This study proposes an optics-based active sensing system for continuous monitoring of underground pipelines in nuclear power plants (NPPs). The proposed system generates and measures guided waves using a single laser source and optical cables. First, a tunable laser is used as a common power source for guided wave generation and sensing. This source laser beam is transmitted through an optical fiber, and the fiber is split into two. One of them is used to actuate macro fiber composite (MFC) transducers for guided wave generation, and the other optical fiber is used with fiber Bragg grating (FBG) sensors to measure guided wave responses. The MFC transducers placed along a circumferential direction of a pipe at one end generate longitudinal and flexural modes, and the corresponding responses are measured using FBG sensors instrumented in the same configuration at the other end. The generated guided waves interact with a defect, and this interaction causes changes in response signals. Then, a damage-sensitive feature is extracted from the response signals using the axi-symmetry nature of the measured pitch-catch signals. The feasibility of the proposed system has been examined through a laboratory experiment.

• Journal of the Korean Society for Nondestructive Testing
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• v.19 no.5
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• pp.369-377
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• 1999

Recently, it is gradually raised necessity that thickness of thin film is measured accuracy and managed in industrial circles and medical world. Ultrasonic signal processing method is likely to become a very powerful method for NDE method of detection of microdefects and thickness measurement of thin film below the limit of ultrasonic distance resolution in the opaque materials, provides useful information that cannot be obtained by a conventional measuring system. In the present research. considering a thin film below the limit of ultrasonic distance resolution sandwiched between three substances as acoustical analysis model, demonstrated the usefulness of ultrasonic signal processing technique using information of ultrasonic frequency for NDE of measurements of thin film thickness. Accordingly, for the detection of delamination between the junction condition of boundary microdefect of thin film sandwiched between three substances the results from digital image processing.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.10
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• pp.353-360
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• 2016

Recently, solar photovoltaic(PV) power generation which generates electrical power from solar panels composed of multiple solar cells, showed the most prominent growth in the renewable energy sector worldwide. However, in spite of increased demand and need for a photovoltaic power generation, it is difficult to early detect defects of solar panels and equipments due to wide and irregular distribution of power generation. In this paper, we choose an optimal machine learning algorithm for estimating the generation amount of solar power by considering several panel information and climate information and develop a defect detection system by using the chosen algorithm generation. Also we apply the algorithm to a domestic solar photovoltaic power plant as a case study.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.3
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• pp.92-99
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• 1999

The inspection unit which is developed and used in this study, is processed the shape data from the CCD camera to seek welding bite section shape, and then calculated as a real dimension from measuring the value of each inspection item. The reason of measuring with the real in this study is came out from the image method which used for a long time, which is extricated the characteristic as the dimension of pixel by recognize pixel. The measurement method of the section shape is that we decide the thresholding value after we drew the histogram to binarizate the object. After that, we make flat the object to get rid of the noise and measure the shape of welded part through the boundarization of the object. The shape measurement is that measure the value of the welding part to adapt the actual operation program from using the ratio between the actual dimension of the standard specimen and the dimension of image, to measure the ratio between the actual product and the camera image. The inspection algorithm which estimates the quality of welded product is developed and also, the software GUI(Graphic User Interface) which processes the automatic test function of the inspection system is developed. We make the foundation of the inspection automatic system and we will help to apply other welding machine.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.6
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• pp.11-16
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• 2021

In this paper, a quality inspection system was developed to identify the defective assembly of connectors used in automobile wiring. For waterproof connectors, an internal seal must be inserted for waterproofing. However, there are cases where it is omitted or double-inserted during production. An automatic inspection jig was designed using photosensors and touch switches to classify good and bad connector components. In the case of the existing visual inspection, 6,400 connectors were inspected when 5 people inspected for 8 hours. However, when using the inspection jig developed under the same conditions, 20,000 pieces were inspected. In other words, the productivity is greatly improved compared to the conventional visual inspection.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2037-2042
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• 2017

The manufacturing facility is generally operated by a pre-set program under the existing factory automation system. On the other hand, the manufacturing facility must decide how to operate autonomously in Industry 4.0. Determining the operation mode of the production facility itself means, for example, that it detects the abnormality such as the deterioration of the facility at the shop-floor, prediction of the occurrence of the problem, detection of the defect of the product, In this paper, we propose a manufacturing process modeling using a queue for detection of manufacturing process abnormalities at the shop-floor, and detect abnormalities in the modeling using SVM, one of the machine learning techniques. The queue was used for M / D / 1 and the conveyor belt manufacturing system was modeled based on ${\mu}$, ${\lambda}$, and ${\rho}$. SVM was used to detect anomalous signs through changes in ${\rho}$.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.9
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• pp.1297-1301
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• 2013

This paper analyzes of PD occurrence position through an analysis of the arrival time difference between the GIS partial discharge signal. Because of GIS (Gas Insulated Switchgear) is a facility very important power equipment and as part of the equipment that make up the power system, the stabilization of the power industry, which accounted for 88.5% share of GIS substation in the form of a substation is an important equipment for power supply. In the situation where we are gradually expanding the need for preventive diagnosis in order to improve the efficiency of equipment management and failure prevention for Preventive diagnosis. In this paper as a method for extracting pre-defect of failure of GIS Apply the average value method of calculating the 5 times each using a pulse of the first time of the second pulse (${\Delta}t$) with an oscilloscope generation position PD(Partial Discharge). the results of GIS internal inspection, the partial discharge of the actual the position of the partial discharge was confirmed with an accuracy of about 82% of positions. Arrival time difference in the most effective manner if the partial discharge of GIS internal occurs by applying the averaging method and TOA(Time of arrival) method, the partial discharge occurs you through the measurement and analysis of PD signal occurs was confirmed in the experiment are presented and diagnostic methods location tracking.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.6
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• pp.529-536
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• 2015

A defect could be generated in bolts for a use of oil filters for the manufacturing process and then may affect to the safety and quality in bolts. Also, fine defects may be imbedded in oil filter system. So it is very important that such defects be investigated and screened during the multiple manufacturing processes. Therefore, in order effectively to evaluate the fine defects, the FEM simulations were performed to make characterization in the crack detection of the bolts and the parameters such as number of turns of the coil, the coil size, applied frequency were calculated based on the simulation results. Simulations were carried out for the defect signal of eddy current probe. Exciter and receiver were utilized. In this paper, the FEM simulations were performed in both bobbin-type and pancake-type probe, both probes were optimized under Eddy current FEM simulations and the results of calculation were discussed.

• Journal of the Korean Wood Science and Technology
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• v.41 no.2
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• pp.164-172
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• 2013

The purpose of this research was development of quantitative ultrasonic test methodology for detecting internal defects in members of ancient wooden building. Connection part between wooden members and/or contacted or hidden part by wall of ceiling or other construction materials make it hard to apply direct way of ultrasonic test. So indirect way of ultrasonic test needed to be applied. Test methodology with newly developed prototype of ultrasonic system was proposed. Homogeneous material with polypropylene was also tested for establishing the criterion. Results showed that TOF(time of flight)-energy and pulse length were found out to be proper ultrasonic parameters for predicting depth of defect in wood different from polypropylene. It was not possible to directly apply prediction equation derived from polypropylene. Newly established prediction equation shows coefficient of determination of 0.73 for wood. Finally, defect of replaced rafter members was predicted with the coefficient of determination of 0.32. Various aspects of ultrasound propagation in wood including anisotropy need to be carefully considered to raise up the prediction accuracy.