• Transactions of the Korean Society of Mechanical Engineers A
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• v.23 no.7 s.166
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• pp.1065-1074
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• 1999

This study proposes the analysis and evaluation method of time series ultrasonic signal using the chaotic feature extraction for ultrasonic pattern recognition. Features extracted from time series data using the chaotic time series signal analysis quantitatively welding defects. For this purpose analysis objective in this study is fractal dimension and Lyapunov exponent. Trajectory changes in the strange attractor indicated that even same type of defects carried substantial difference in chaoticity resulting from distance shills such as 0.5 and 1.0 skip distance. Such differences in chaoticity enables the evaluation of unique features of defects in the weld zone. In experiment fractal(correlation) dimension and Lyapunov exponent extracted from 6dB ultrasonic defect signals of weld zone showed chaoticity. In quantitative chaotic feature extraction, feature values(mean values) of 4.2690 and 0.0907 in the case of porosity and 4.2432 and 0.0888 in the case of incomplete penetration were proposed on the basis of fractal dimension and Lyapunov exponent. Proposed chaotic feature extraction in this study enhances ultrasonic pattern recognition results from defect signals of weld zone such as vertical hole.

• Journal of Welding and Joining
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• v.28 no.1
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• pp.66-71
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• 2010

With large specific strength and outstanding corrosion resistance and erosion resistance in sea water, titanium and titanium alloy are widely used in heat exchanger production. In particular, pure titanium demonstrates outstanding molding performance and may be considered optimal for production of heat exchanger. Since titanium is very vulnerable to oxidation and embrittlement during welding, processes with less heat input are widely used, and laser welding is widely applied by considering production performance and shield etc in atmosphere. So far, 1st report and 2nd report compared and analyzed embrittlement degrees by bead colors of weldment through oxygen and nitrogen quantitative analysis and hardness measurement, and evaluated welding performance and mechanical properties of butt welding. This study evaluated field applicability of lap welding to heat exchange plate of LPG re-liquefaction device for ships through tensile stress test, hardness test and internal pressure test etc after deducing optimal weding condition and applying to actual heat exchange plate. In bead overlap area, the experiment produced sound welds with no porosity or defect by increasing and decreasing laser power, and tensile-shear test results indicated virtually the same tension and yield strength as base metal. As a result of measuring hardness at lateral cross section and bead overlap zone of actual heat exchanger welds, hardness difference within 20Hv was produced at base metal, HAZ and weldment, and as a result of pneumatic and hydraulic pressure test, no leakage occurred.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.185-192
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• 2021

Various methods have been proposed to determine the defect detection of welding bead, and recently sensor data and image data inspection have been steadily announced. There are advantages that sensor data inspection is highly accurate, and two-dimensional-based image data inspection is able to determine the position of the welding bead. However, when analyzing only with sensor data, it is difficult to determine whether the welding has been performed at the correct position. On the other hand, the image data inspection does not have high accuracy due to noise and measurement errors. In this paper, we propose a method that can complement the shortcomings of each inspection method and increase its advantages to improve accuracy and speed up inspection by fusing sensor data inspection which are average current, average volt, and mixed gas data, and image data inspection methods and is implemented as software. In addition, it is intended to allow users to conveniently and intuitively analyze and grasp the results by performing analysis using a graphical user interface(GUI) and checking the data and inspection results used for the inspection. Sensor inspection is performed using the characteristics of each sensor data, and image data is inspected by applying a morphology geodesic active contour algorithm. The experimental results showed 98% accuracy, and when performing the inspection on the four image data, and sensor data the inspection time was about 1.9 seconds, indicating the performance of software that can be used as a real-time inspector in the welding process.

• Journal of Welding and Joining
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• v.13 no.2
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• pp.42-52
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• 1995

In the evaluation of aging degradation on the structural materials based on the fracture mechanics, the detection and size prediction of defect are very important. Aiming at nondestructive detection and size prediction ol defect with high accuracy and resolution, therefore, an lnduced Current Focusing Potential Drop(ICFPD) technique has been developed. The principle of this technique is to induce a focusing current at an exploratory region by an induction wire flowing an alternating current(AC) that is a constant ampere and frequency. Defects are assessed with the potential drops that are measured the induced current on the surface of metallic material by the potential pick-up pins. In this study, the lCFPD technique was applied for evaluating the location and size of the surface crack and blind crack made in plate specimens, and also for detecting the defects existing in valve, a field component, that were developed by SCC etc. during the service. The results of this present study show that surface crack and blind crack are able to defect with potential drop. these cracks are distinguished with the distribution of potential drop, and the crack depths can be estimated with each normalized potential drop that are parameters estimating the depth of each type crack. In the field component, the defects estimated by experiment result correspond with those in the cutting face of the measuring point within a higher sensitivity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1086-1103
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• 2020

The automatic identification and classification of image-based weld defects is a difficult task due to the complex texture of the X-ray images of the weld defect. Several depth learning methods for automatically identifying welds were proposed and tested. In this work, four different depth convolutional neural networks were evaluated and compared on the 1631 image set. The concavity, undercut, bar defects, circular defects, unfused defects and incomplete penetration in the weld image 6 different types of defects are classified. Another contribution of this paper is to train a CNN model "RayNet" for the dataset from scratch. In the experiment part, the parameters of convolution operation are compared and analyzed, in which the experimental part performs a comparative analysis of various parameters in the convolution operation, compares the size of the input image, gives the classification results for each defect, and finally shows the partial feature map during feature extraction with the classification accuracy reaching 96.5%, which is 6.6% higher than the classification accuracy of other existing fine-tuned models, and even improves the classification accuracy compared with the traditional image processing methods, and also proves that the model trained from scratch also has a good performance on small-scale data sets. Our proposed method can assist the evaluators in classifying pipeline welding defects.

• Proceedings of the KWS Conference
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• 2009.11a
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• pp.32-32
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• 2009

Electric Resistance Welding (ERW) process is the most efficient process to manufacture the linepipe. To develop the high performance ERW linepipe using the high strength and the high alloy steels, the modulation of input power waveform such as sinusoidal waveform is introduced because the conventional ERW technology is not sufficient enough to produce the high quality linepipe due to its strength and high alloy contents (high Ceq). In this article, the material used for the experiment was API X60 with 8.2mm thickness, and ERW simulator at POSCO was used to develop a waveform control system for the power modulation. The frequency of power modulation was varied from 50Hz to 150Hz with the fixed amplitude of ${\pm}2%$ power. The non-modulated power input and the modulated power input cases are conducted to demonstrate the variation of the narrow gap length and the arcing frequency due to power modulation. From results of the non-modulated power input case, the excessive power causes the longer narrow gap length and the low arcing frequency due to the large heat input and the strong electro magnetic force that increase the weld defect. On the contrary, the small narrow gap length and the high arcing frequency reduce the weld defect. After modulating the power input with 50Hz and 100Hz at the fixed power, the arcing frequency increases, but the narrow gap length does not change much. The high arcing frequency prevents the formation of weld defect because the sweeping frequently cleans the oxides on the narrow gap edges. As a result, the manufacturing window can be expanded by the power modulation that provides the stable ERW process for the quality improvement of the linepipe made from the high strength/high alloy steels.

• Journal of the Korean Society for Nondestructive Testing
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• v.28 no.4
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• pp.323-330
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• 2008

High cycle bending fatigue of socket welded small bore pipe was characterized, and also the fatigue crack initiation of small bore pipe was monitored in situ by the acoustic emission (AE) technique. The STS 316L stainless steel specimens were prepared by gas tungsten arc welding (GTAW) process having the artificial defect (i.e., lack of penetration) and defect free at the root. The fatigue failure was occurred at the loc for high stress and root for relatively low stress. The crack initiation cycles ($N_i$) was defined to the abrupt increase in AE counts during the fatigue test, and then the cracks were observed by the radiographic test and electron microscope before and after the fatigue crack initiation cycles. The socket welded pipe damaged by bending fatigue was studied regarding the welding defect, failure mode, and crack initiation cycles for the diagnosis and monitoring.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.107-116
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• 2024

Copper Filter Dryer (CFD) are responsible for removing impurities from the circulation of refrigerant in refrigeration and cooling systems to maintain clean refrigerant, and defects in CFD can lead to product defects such as leakage and reduced lifespan in refrigeration and cooling systems, making quality assurance essential. In the quality inspection stage, human inspection and defect judgment methods are traditionally used, but these methods are subjective and inaccurate. In this paper, YOLOv7 object detection algorithm was used to detect defects occurring during the CFD Shaft pipe and welding process to replace the existing quality inspection, and the detection performance of F1-Score 0.954 and 0.895 was confirmed. In addition, the cause of defects occurring during the welding process was analyzed by analyzing the sensor data corresponding to the Timestamp of the defect image. This paper proposes a method for manufacturing quality assurance and improvement by detecting defects that occur during CFD process and analyzing their causes.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.5
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• pp.135-143
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• 2000

The vision system is easy to use the exclusive use as a independent computer system but it is not much popularization by reason of expensive and difficult to adapt to the various fields, because it is easy to the existed computer system, the price is cheap and also it can use to the various measurement purpose which user wanted and programed. The measurement method of the vehicle axle casing nut welding part is that measure the value of the welding part to adapt the actual operation program from using the ratio between the actual length of the standard specimen and the length of image, to measure the ratio between the actual product and the camera image. A defect is found by the assembled visual inspection system. The inspection algorithm which estimates the quality of welded product is developed and also, the software program which processes the automatic test function of the inspection system. We make the foundation of the inspection automatic system and we will help to apply other welding machine.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.05a
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• pp.425-431
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• 1999

We develope plasma monitoring system which detect plasma signals and store them for Laser welding quality evaluation and analysis using photo detector. The most fundamental and important aspects in such a system are signal restoration fidelity, noise immunity and noise cancelation capability. In this paper, we propose implementation method using distribute processing structure and hybrid digital communication for high noise cancelation capability, immunity and signal fidelity which are poorly presented in other researches. Lab experimental results and welding experimental results show a effectiveness of proposed method and plasma data is stored with 256 kbps without any communication error. we are implementing various welding defect recognition algorithm in this system.