• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.5
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• pp.103-110
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• 2008

A reliable extraction of welded area is the precedent task before the detection of weld defects in industrial radiography. This paper describes an attempt to detect and extract the welded features of steel tubes from the computed radiography(CR) images. The statistical properties are first analyzed on over 160 sample radiographic images which represent either weld or non-weld area to identify the differences between them. The analysis is then proceeded by pattern classification to determine the clustering parameters. These parameters are the width, the functional match, and continuity. The observed weld image is processed line by line to calculate these parameters for each flexible moving window in line image pixel set. The local statistic line-clustering method is used as the classifier to recognize each window data as weld or non-weld cluster. The sequential procedure is to track the edge lines between two distinct regions by iterative calculation of threshold, and it results in extracting the weld feature. Our methodology is concluded to be effective after experiment with CR weld images.

• Journal of Welding and Joining
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• v.16 no.3
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• pp.64-73
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• 1998

This paper is concerned with defects detection and evaluation of heat affected zone (HAZ) in austenitic stainless steel type 304 by ultrasonic wave and neural network. In experiment, the reflected ultrasonic defect signals from artificial defects (side hole, vertical hole, notch) of HAZ appears as beam distance of prove-defect, distance of probe-surface, depth of defect-surface on CRT. For defect classification simulation, neural network system was organized using total results of ultrasonic experiment. The organized neural network system was learned with the accuracy of 99%. Also it could be classified with the accuracy of 80% in side hole, and 100% in vertical hole, 90% in notch about ultrasonic pattern recognition. Simulation results of neural network agree fairly well with results of ultrasonic experiment. Thus were think that the constructed system (ultrasonic wave - neural network) in this work is useful for defects dection and classification such as holes and notches in HAZ of austenitic stainless steel 304.

• Tribology and Lubricants
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• v.30 no.2
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• pp.124-129
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• 2014

The piping system accounts for a large portion of the machinery structure of a plant, and is considered as a very important mechanical structure for plant safety. Accordingly, it is used in most energy plants in the nuclear, gas, and heavy chemical industries. In particular, the piping system for a nuclear plant is generally complicated and uses the reactor and its cooling system. The piping equipment is exposed to diverse loads such as weight, temperature, pressure, and seismic load from pipes and fluids, and is used to transfer steam, oil, and gas. In ultrasound infrared thermography, which is an active thermography technology, a 15-100 kHz ultrasound wave is applied to the subject, and the resulting heat from the defective parts is measured using a thermography camera. Because this technique can inspect a large area simultaneously and detect defects such as cracks and delamination in real time, it is used to detect defects in the new and renewable energy, car, and aerospace industries, and recently, in piping defect detection. In this study, ultrasound infrared thermography is used to detect information for the diagnosis of nuclear equipment and structures. Test specimens are prepared with piping materials for nuclear plants, and the optimally designed ultrasound horn and ultrasound vibration system is used to determine damages on nuclear plant piping and detect defects. Additionally, the detected images are used to improve the reliability of the surface and internal defect detection for nuclear piping materials, and their field applicability and reliability is verified.

• Journal of the Korean Society for Railway
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• v.5 no.2
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• pp.55-60
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• 2002

This study proposes the post-processor simulator construction of ultrasonic signal for integrity evaluation of railway truck. For these purposes, the ultrasonic signals for defects(crack) of weld zone in frames are acquired in the type of time series data and echo strength. The detection of the natural defects in railway truck is performed using the characteristics of echodynamic pattern in ultrasonic signal. The constructed post-processor simulator agree fairly well with the measured results of test block(defect location, beam propagation distance, echo strength, etc). Proposed post-processor simulator construction of ultrasonic in this study can be used for the integrity evaluation of railway truck.

• 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 Institute of Control, Robotics and Systems
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• v.11 no.7
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• pp.595-601
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• 2005

A mobile robot system utilizing NDT (Non-Destructive Testing) method is designed and fabricated f3r automatic integrity evaluation of large sized industrial reservoirs and pipelines. The developed mobile robot can crawl over the outer surface of the industrial facilities even though the shape of the structures is various and unsymmetric. The robot detects defects such as pinholes, cracks and thickness reduction at the wall of the facilities using EMAT (Electro-Magnetic Acoustic Transducer). Image processing technology for weld line detection at the surface of the target and host programs including defect detecting algorithms are also developed. Automation of defect detection for these kinds of large facilities using mobile robots is helpful to prevent significant troubles of the structures without danger of human beings under harmful environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2486-2491
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• 2013

There are invisible defects by naked eyes in ceramic material images such as internal stomata, cracks and foreign substances. In this paper we propose a method to detect and extract such defects from ceramic pipe weld zone by applying ART2 learning. In pre-processing, we apply Ends-in Search Stretching to enhance the intensity and then perform fuzzy binarization with triangle type membership function followed by enhanced ART2 that interacts with random input patterns to extract such invisible defects. The experiment verifies that this proposed method is sufficiently effective.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.1
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• pp.43-48
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• 2020

At present, 24 nuclear power plants are in operation nationwide as the main power source responsible for about 27% of Korea's electricity, and five nuclear power plants are currently under construction. Issues of nuclear safety and reliability have always existed, but after the Fukushima accident, ensuring reliability has become an even more important issue for safety. Compared to other kinds of accidents, the initial response after a nuclear accident is more important than any other accident. Prior to accidents, it is important to be able to predict and judge the accident in advance for the sake of prevention. In this research, non-destructive inspection methods for existing pipe welds include radiographic, ultrasonic, magnetic particle practice, and liquid penetration testing. For this experiment, carbon steel pipes like that of the material used in nuclear pipes were adopted, and specimen welded to the flange (Flange) were manufactured. After testing, the weld specimen were not damaged through the infrared thermography (IRT) experiment. This study attempted to improve the safety of carbon steel pipes through a comparative analysis of finite element analysis.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.7 no.2
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• pp.21-25
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• 2011

Although many defects in PZR heater sleeve have been reported continually from operating experiences in oversea nuclear power plant, utilities get into difficulties in finding appropriate methods for diagnostics of the components due to the limited access or high radiation problems. Recently, as an alternative, diagnostics using Guided Wave Testing(GWT) are proposed and the attention of the methods has been growing gradually because of their long range inspection capability. This study is to investigate the effectiveness of GWT to detect PWSCC in welding points of PZR heater sleeve. Moreover, mode sensitivity analysis of GWT and optimal frequency for the diagnostics of PWSCC are presented by testing the mock-ups specimens that contain artificial flaws.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.11
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• pp.6432-6439
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• 2014

The NAUT (Non-contact Air coupled Ultrasonic Testing) technique is one of the ultrasonic testing methods that enables non-contact ultrasonic testing by compensating for the energy loss caused by the difference in acoustic impedance of air with an ultrasonic pulser receiver, PRE-AMP and high-sensitivity transducer. As the NAUT is performed in a state of steady ultrasonic transmission and reception, testing can be performed on materials of high or low temperatures or specimens with a rough surface or narrow part, which could not have been tested using the conventional contact-type testing technique. For this study, the internal defects of spot weld, which are often applied to auto parts, and CFRP parts, were tested to determine if it is practical to make the NAUT technique commercial. As the spot welded part had a high ultrasonic transmissivity, the result was shown as red. On the other hand, the part with an internal defect had a layer of air and low transmissivity, which was shown as blue. In addition, depending on the PRF (Pulse Repetition Frequency), an important factor that determines the measurement speed, the color sharpness showed differences. With the images obtained from CFRP specimens or an imaging device, it was possible to identify the shape, size and position of the internal defect within a short period of time. In this paper, it was confirmed in the above-described experiment that both internal defect detection and image processing of the defect could be possible using the NAUT technique. Moreover, it was possible to apply NAUT to the detection of internal defects in the spot welded parts or in CFRP parts, and commercialize its practical application to various fields.