Development of a New Optical Monitoring System of Welding Conditions for Producing HF-ERW Line Pipes With High Weld Seam Toughness: Advanced Welding Process of HF-ERW 2

2012 ◽  
Author(s):  
Noboru Hasegawa ◽  
Hideki Hamatani ◽  
Nobuo Mizuhashi ◽  
Toshisuke Fukami ◽  
Yoshifumi Karube ◽  
...  
Keyword(s):  
Image Processing ◽  
Monitoring System ◽  
Weld Seam ◽  
Measurement Techniques ◽  
Welding Process ◽  
Impedance Measurement ◽  
Input Power ◽  
Welding Condition ◽  
Convergence Angle

To improve the weld seam quality of HF-ERW (high frequency-electric resistance welded) pipes, a monitoring system that combines optical and electrical measurement techniques is developed. In the welding process, it is known that there are type 1, 2, and 3 phenomena depending on the welding speed, the input power and the Vee convergence angle. We found that type 2 phenomena can be subdivided into three conditions, normal type 2, instable (type 3) and the two phased reduction of the Vee convergence angle (type 2′) regions in production processes, caused by the facing angle of the edge surfaces, which may not have the I-shape. Among them, only the condition under a narrow range of type 2′ allows to prove melting in the whole area of the edge surfaces and to excrete the oxide inclusions from the weld seam. Following the welding mechanism, the defect rate in the weld seam is kept at minimum. Accordingly, we developed a monitoring system to control the welding condition to the type 2′ range. An optical image processing and an electric impedance measurement method are combined into this system, which is based on remote photographing, high-precision V point detection, temperature measurement techniques with image processing, and a multi-frequency filtering method of the transient impedance waveform. Furthermore, operational indices are constructed through the analysis of the welding mechanism and the experimental data. We find that the weld defect area ratio lower than ever is steadily achieved in the trial products, as a result of continuously controlling the heat-input condition.

Development of the New Welding Control Method for HF-ERW Pipes: Advanced Welding Process of HF-ERW 1

2012 ◽  
Author(s):  
Toshisuke Fukami ◽  
Nobuo Mizuhashi ◽  
Noboru Hasegawa ◽  
Hideki Hamatani ◽  
Yasushi Hasegawa ◽  
...  
Keyword(s):  
Heat Input ◽  
Manufacturing Process ◽  
Weld Seam ◽  
Input Power ◽  
Area Ratio ◽  
Welding Heat Input ◽  
Defect Area ◽  
Welding Defect ◽  
Melted Metal

In recent years, the key application requirement of the ERW line pipe has been its toughness, including the weld seam. It is known that, among defects generated at the weld seam, the penetrator defect affects toughness and is difficult to control by welding condition[1–4]. Generally speaking, ERW pipes are welded with exposure to air, and oxides are produced on the surface of the melted metal during the process. The discharge of this melted metal by electromagnetic force and squeezing produced at the current welding route is effective in eliminating the penetrator, and constantly optimizing the welding heat input means this defect can be constantly reduced. To optimize the welding heat input, therefore, it is important to determine the welding phenomena occurring at the welding spot and contrast them with the defect area ratio. We have studied (examined) the welding phenomena, optimum heat input power and the welding defect generation mechanism. Consequently, it was revealed that by varying the welding speed, Vee convergence angle and welding heat input, etc., a new categorization of welding phenomena as Types 1, 2, 3, and 2′ was possible. In the case of Type 2 and 2′ welding phenomena, the welding defect area ratio decreases, which resulted in a sound seam weld with high toughness. If these two welding phenomena are compared, the wider heat input power range of Type 2′ is preferable for the HF-ERW manufacturing process. The higher heat input of Type 2′ compared to Type 2 compensates for the abutting surface angle fluctuation, meaning it is also preferable for pipe manufacturing. Consequently, the control of the Type 2′ welding phenomenon is preferable for the HF-ERW manufacturing process.

scholarly journals Force feedback-based quality monitoring of the friction stir welding process utilizing an analytic algorithm

2020 ◽  
Author(s):  
P. Rabe ◽  
A. Schiebahn ◽  
U. Reisgen
Keyword(s):  
Friction Stir Welding ◽  
Monitoring System ◽  
Force Feedback ◽  
Weld Seam ◽  
Position Control ◽  
Welding Process ◽  
Quality Monitoring ◽  
Welding Parameters ◽  
Process Data ◽  
Friction Stir

AbstractThe friction stir welding (FSW) process is known as a solid-state welding process, comparatively stable against external influences. Therefore, the process is commonly used with fixed welding parameters, utilizing axial force control or position control strategies. External and internal process disturbances introduced by workpiece, gap tolerance, tool wear, or machine/tool inadequacies are rarely monitored, and conclusions about the weld seam quality, based on the recorded process data, are not drawn. This paper describes an advancement, improving on research into the correlation of process force feedback events or gradual force changes and the resulting weld seam characteristics. Analyzing the correlation between examined weld sections and high-resolution rate force data, a quality monitoring system based on an analytic algorithm is described. The monitoring system is able to accurately distinguish sound welds from such with internal (void) and external (flash) defects.

A Study on Modified Hough Algorithm for Image Processing in Weld Seam Tracking System

2015 ◽  
Vol 1088 ◽  
pp. 824-828 ◽  
Author(s):  
Jong Pyo Lee ◽  
Qian Qian Wu ◽  
Min Ho Park ◽  
Cheol Kyun Park ◽  
Ill Soo Kim
Keyword(s):  
Image Processing ◽  
Weld Seam ◽  
Gma Welding ◽  
Vision System ◽  
Tracking System ◽  
Computing Time ◽  
Weld Line ◽  
Welding Process ◽  
Seam Tracking ◽  
Weld Seam Tracking

In modern market, achieving mechanical and automatic arc welding process is the key issue to be solved in welding industries. Because of the high complexity of the welding environment, manual detection of the weld line information is hard to be successful and time consuming. Therefore, this study aim at developing a new image processing algorithm for seam tracking system in Gas Metal Arc (GMA) welding by modified Hough algorithm based on the laser vision system. Firstly, noises in the captured weld seam images by CCD camera were effectively removed by noise filtering algorithm and then weld joint position were detected by the modified Hough algorithm to realize the automatic weld seam tracking. To verify the efficiency of the developed image processing model, a common image processing method was employed and the processed results were compared with the proposed algorithm. Statistical results proved that the modified Hough algorithm was able to acquire the weld information precisely with less computing time and memory cost, which also capable for industrial application.

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