• Proceedings of the KSR Conference
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• 1998.11a
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• pp.87-95
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• 1998

This study proposes the analysis and evaluation method of time series ultrasonic signal using the attractor analysis. Features extracted from time series signal analyze quantitatively characteristics of welding defects. For this purpose, analysis objective in this study is fractal dimension and attractor Quadrant feature. Trajectory changes in the attractor indicated that even the same type of defects carried substantial difference in fractal characteristics resulting from distance shifts such as parts of head and flange. Such differences in characteristics of weld defects enables the evaluation of unique features of defects in the weld zone. In quantitative fractal feature extraction, feature values of 3.848 in the case of part of head(crack) and 4.102 in the case of part of web(side hale) and 3.711 in the case of part of flange(crack) were proposed on the basis of fractal dimensions. Proposed attractor feature extraction in this study can enhance the precision rate of ultrasonic evalaution for defect signals of rail weld zone such as side hole and crack.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.1
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• pp.99-104
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• 2010

Magnesium and magnesium alloys, the lightest structural materials, have been received plenty of global attention recently. These alloys could be applied in various fields, especially the electronics industry, because of their excellent electromagnetic interference shielding. However, the welding technique of magnesium alloys has not been established. This study is related to the welding of AZ31B magnesium alloy by a short-pulsed a Nd:YAG laser. Two types of pulse waves, square pulse and variable pulse, were used to control weld defects. Results show that the crack and porosity, generated in the weld, had not been controlled by general square pulse. But through the application of variable pulse, the defects could be prevented and the good weld zone was obtained.

• Journal of Welding and Joining
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• v.21 no.1
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• pp.60-65
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• 2003

At present. welding of most pipes with large diameter is carried out by the manual process. Automation of the welding process is necessary f3r the sake of consistent weld quality and improvement in productivity. In this study, two vision sensors, based on the optical triangulation, were used to obtain the information for seam tracking and detecting the weld defects. Through utilization of the vision sensors, noises were removed, images and 3D information obtained and positions of the feature points detected. The aforementioned process provided the seam and leg position data, calculated the magnitude of the gap, fillet area and leg length and judged the weld defects by ISO 5817. Noises in the images were removed by using the gradient values of the laser stripe's coordinates and various feature points were detected by using an algorithm based on the iterative polygon approximation method. Since the process time is very important, all the aforementioned processes should be conducted during welding.

• Laser Solutions
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• v.3 no.2
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• pp.53-61
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• 2000

On the laser weld production line, a slight alteration of the welding condition produces many defects. The defects are monitored in real time, in order to prevent continuous occurrence of defects, reduce the loss of material, and guarantee good quality. The measurement system is produced by using three photo-diodes for detection of the plasma and spatter signal in CO$_2$ laser welding. For high speed CO$_2$ laser welding, laser tailored welded blanks for example, on-line weld quality monitoring system was developed by using fuzzy multi-feature pattern recognition. Weld qualities were classified optimal heat input, a little low heat input, low heat input, and focus misalignment, and final weld quality were classified good and bad.

• Journal of Welding and Joining
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• v.9 no.4
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• pp.60-68
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• 1991

The weld quality of end cap welds in Pressurized Heavy Water Reactor (PHWR) Fuel is extremely important for the fuel performance in the nuclear reactor. The quality of resistance upset welds is currently evaluated mainly by the metallographic examination although it reveals only two weld cross-sections in a circumference welds. This investigation was, firstly, carried out to determine whether the ultrasonic examination would be applied to detect weld defects in the end cap welds and, secondly, to measure the mechanical strength of upset butt welds as a function of phase shift percentage. The major results obtained in this study are as follows: 1. The weld current and amount of upset shrinkage linearly increased with increasing the phase shift percentage. 2. Above the phase shift 55%, the defects in the welds were completely eliminated with increasing the phase of sound weld was over the thickness of cladding tube. 3. The ultrasonic testing well detected such defects in the end cap welds as upset external crack, upset split, corner crack and irregular weld flash comparing with the results of metallography. 4. The micro-fissure in the corner of the end cap welds was reliably detected by ultrasonic testing. 5. The mechanical strength in the welds increased with increasing phase shift percentage but the fracture did't occur in the welds above 55%.

• Journal of the Korean Society for Railway
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• v.2 no.2
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• pp.21-30
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• 1999

This study proposes the analysis and evaluation method of time series ultrasonic signal using the phase space-frequency domain. Features extracted from time series signal analyze quantitatively characteristics of weld defects. For this purpose, analysis objectives in this study are features of time domain and frequency domain. Trajectory changes in the attractor indicated a substantial difference in fractal characteristics resulting from distance shifts such as parts of head and flange even though the types of defects are identified. These differences in characteristics of weld defects enables the evaluation of unique characteristics of defects in the weld zone. In quantitative fractal feature extraction, feature values of 3.848 in the case of part of head(crack) and 4.102 in the case of part of web(side hole) and 3.711 in the case of part of flange(crack) were proposed on the basis of fractal dimension. Proposed phase space-frequency domain method in this study can integrity evaluation for defect signals of rail weld zone such as side hole and crack.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.8
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• pp.1270-1278
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• 2004

This paper describes the effectiveness of laser pulse shaping in eliminating weld defects such as porosity, cracks and undercuts in pulsed Nd:YAG laser welding. A large porosity was formed in a keyhole mode of deeply penetrated weld metal of any stainless steel. Solidification cracks were present in STS 310S with above 0.017%P and undercuts were formed in STS 303 with about 0.3%S. The conditions for the formation of porosity were determined in further detail in STS 316. With the objectives of obtaining a fundamental knowledge of formation and prevention of weld defects, the fusion and solidification behavior of a molten puddle was observed during laser spot welding of STS 310S through a high speed video photographing technique. It was deduced that cellular dendrite tips grew rapidly from the bottom to the surface, and consequently residual liquid remained at the grain boundaries in wide regions and enhanced the solidification cracking susceptibility. Several laser pulse shapes were investigated and optimum pulse shapes were proposed for the reduction and prevention of porosity and solidification cracking.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.6
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• pp.167-174
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• 1998

The ultrasonic test is recognized for its significance as a non-destructive testing method to detect volume defects such as porosity and incomplete penetration which reduce strength in the weld zone. This paper illustrates the defect detection in the weld zone of ferritic carbon steel using ultrasonic wave and the evaluation of pattern recognition by chaotic feature extraction using time series signal of detected defects as data. Shown in the time series data were that the time delay was 4 and the embedding dimension was 6 which indicate the geometric dimension of the subject system and the extent of information correlation. Based on fractal dimension and lyapunov exponent in quantitative chaotic feature extraction, feature value of 2.15, 0.47 is presented for porosity and 2.24, 0.51 for incomplete penetration The precision rate of the pattern recognition is enhanced with these values on the total waveform of defect signal in the weld zone. Therefore, we think that the ultrasonic pattern recognition method of weld zone defects of ferritic carbon steel by ultrasonic-chaotic feature extraction proposed in this paper can boost precision rate further than the existing method applying only partial waveform.

• Journal of Welding and Joining
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• v.20 no.5
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• pp.87-92
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• 2002

Weldability of Friction Stir Welded(FSW) AZ31B-H24 Mg alloy sheet with 4m thick was evaluated by changing welding speed. The sound welding conditions mainly depended on the suffiicient welding heat input during the process. The insufficient heat input resulted in the void like defect in the weld zone. Higher welding speed caused a larger inner void or lack of bonding. The defects were distributed at the stir zone or the transition region between stir zone and thermo-mechanical affected zone (UE). The size of defects slightly increased with increasing welding speed. These defects had a great effect on the joint strength of weld zone. The weld zone was composed of stir zone, TMAZ and heat affected zone. The stir zone was cosisted of fine recrystallized structure with $5-8\mu\textrm{m}$ in the mean grain size. The hardness of weld zone was near the 60HV, which was slightly lower than that of base metal. The maximum joint strength was about 219MPa that was 75% of that of base metal and the yield strength was also lower than that of base metal partly due to the existance of defects.

• Proceedings of the KWS Conference
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• 1996.10a
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• pp.139-141
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• 1996

Among various welding parameters, the welding current which is inversely proportional to the tip-to-workpiece distance in GMAW is an essential parameter to monitor the GMAW process of horizontal fillet joints. For the case of weld defect such as overlap in horizontal fillet welding, therefore, the signal processing for process monitoring or automatic seam tracking should be modified by considering the weld pool surface geometry including the corresponding weld defect. In other words, the adequate signal processing algorithm is indispensible to improve the performance of the arc sensor. However, arc sensor algorithm already developed usually focus on weld seam tracing but do not considering the weld qualities. In this paper, various experiments were carried out to investigate the tendencies of the weld defects when weaving motion is added, and the experimental method based on 2$^n$ factorial design was proposed for deriving the mathematical model between the leg length and the various welding conditions. Moreover, a signal processing method based on the artificial neural network(Adaptive Resonance Theory) was proposed far discriminating the current signal of sound weld beads from that of weld beads with overlap. Finally, the algorithm for weld seam tracking combined with the mathematical modeling and the signal processing method was carried out to track the weld line in conjunction with the improvement of the weld qualities. The reliability of the proposed algorithms were evaluated through various experiments, which showed that the proposed algorithms could be effectively used for arc welding automation.