• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.94.1-94
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• 2001

Arc sensor gives important groove information during welding. Automatic seam tracking control system with arc sensor has significant characteristics such that bead formation is given as decentralization of penetration and formation of concave bead profile and that a turning point of transverse weaving with constant arc length control is decided whether or not torch height reaches to a specified setting level. Furthermore, the rotating action of the arc prevents hanging of weld bead and forms flat bead surface under high speed welding condition. The variation of groove and deposition area can be detected from the trace of weaving. The area and width of weaving trace has close correlation with the area of groove and deposition. In this paper, main object of this system is to realize an adaptive microprocessor based controller ...

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.6
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• pp.71-78
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• 2007

There have been continuous efforts to automate welding processes. This automation process could be said to fall into two categories, weld seam tracking and weld quality evaluation. Recently, the attempts to achieve these two functions simultaneously are on the increase. For the study presented in this paper, a vision sensor is made, and using this, the 3 dimensional geometry of the bead is measured in real time. For the application in welding, which is the characteristic of nonlinear process, a fuzzy controller is designed. And with this, an adaptive control system is proposed which acquires the bead height and the coordinates of the point on the bead along the horizontal fillet joint, performs seam tracking with those data, and also at the same time, controls the bead geometry to a uniform shape. A communication system, which enables the communication with the industrial robot, is designed to control the bead geometry and to track the weld seam. Experiments are made with varied offset angles from the pre-taught weld path, and they showed the adaptive system works favorable results.

• Journal of Sensor Science and Technology
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• v.33 no.3
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• pp.179-184
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• 2024

In the car industry, welding is a fundamental linking technique used for joining components, such as steel, molds, and automobile parts. However, accurate inspection is required to test the reliability of the welding components. In this study, we investigate the detection of weld beads using 2D image processing in an automatic recognition system. The sample image is obtained using a 2D vision camera embedded in a lighting system, from where a portion of the bead is successfully extracted after image processing. In this process, the soot removal algorithm plays an important role in accurate weld bead detection, and adopts adaptive local gamma correction and gray color coordinates. Using this automatic recognition system, geometric parameters of the weld bead, such as its length, width, angle, and defect size can also be defined. Finally, on comparing the obtained data with the industrial standards, we can determine whether the weld bead is at an acceptable level or not.

• Journal of Welding and Joining
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• v.16 no.1
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• pp.98-105
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• 1998

The accuracy of the finite element method depends upon the mesh that is used in the analysis. The temperature around the arc is higher than the melting point of the materials, and it drops sharply in the regions just away from the arc. This requires an extremely fine mesh in the confined high temperature region to predict the temperature accurately in that region. But the computational time increases with the fineness of mesh. Since fine mesh is required only around the arc source, adaptivity of the input mesh according to the position of the arc source is efficient. The remeshing technique gives a fine mesh in the high temperature region around the arc and a coarse mesh in other region at any time step. With this it is possible to achieve desired accuracy with less computation time. In this study a transient adaptive mesh, remeshing technique, is developed and calculated temperature for a sample problem.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.5
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• pp.70-75
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• 1999

Adaptive control in the robotic GMA(Gas Metal Arc) welding is employed to monitor the information about weld characteristics and process paramters as well as modification of those parameters to hold weld quality within the acceptable limits. Typical characteristics are the bead geometry composition micrrostructure appearance and process parameters which govern the quality of the final weld. The main objectives of this paper are to realize the mapping characteristicso f penetration through the learning. After learning the neural network can predict the pene-traition desired from the learning mapping characteristic. The design parameters of the neural network estimator(the number of hidden layers and the number of nodes in a layer) were chosen from an error analysis. partial-penetration single-pass bead-on-plate welds were fabricated in 12mm mild steel plates in order to verify the performance of the neural network estimator. The experimental results show that the proposed neural network estimator can predict the penetration with reasonable accuracy and gurarantee the uniform weld quality.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.608-610
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• 2004

In continuous annealing line (CAL), POSCO, the center position control (CPC) is an essential technique that renders the steel-strip to pass at the center of a roll in order to prevent the strip from skewing or breaking. The CPC algorithm currently installed on the steering roll in the heating section of CAL is to control the strip position by using the reverse phase of error from the center position, without considering the dynamics of strip horizontal movement. Such algorithm may, unfortunately, require a manual operation occasionally when the range of strip input becomes wide, causing the dynamics 0 be dominant. Other PID-type control is rarely used in automatic operation because the excess of response may occur when the discontinuous points such as welding joints pass through rolls. In this paper, we identify the CPC system by using off-line data and design a compensator for the excessive dynamics by using the adaptive inverse control. Simulation result depicts the improved reliability of the proposed CPC system.

• Journal of Computational Design and Engineering
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• v.2 no.4
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• pp.261-267
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• 2015

Free-form blades are widely used in different industries, such as aero-engine and steam turbine. Blades that are damaged during service or have production deficiencies are usually replaced with new ones. This leads to the waste of expensive material and is not sustainable. However, material and costs can be saved by repairing of locally damaged blades or blades with localized production deficiencies. The blade needs to be further machined after welding process to reach the aerodynamic performance requirements. This paper outlines an adaptive location approach of repaired blade for model reconstruction and NC machining. Firstly, a mathematical model is established to describe the localization problem under constraints. Secondly, by solving the mathematical model, localization of repaired blade for NC machining can be obtained. Furthermore, a more flexible method based on the proposed mathematical model and the continuity of the deformation process is developed to realize a better localization. Thirdly, by rebuilding the model of the repaired blade and extracting repair error, optimized tool paths for NC machining is generated adaptively for each individual part. Finally, three examples are given to validate the proposed method.

• Structural Engineering and Mechanics
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• v.88 no.3
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• pp.239-249
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• 2023

The Radial Point Interpolation Method (RPIM) has been proposed to overcome the difficulties associated with the use of the Radial Basis Functions (RBFs). The RPIM has the following properties: Simple implementation in terms of boundary conditions as in the Finite Element Method (FEM). A less expensive CPU time compared to other collocation meshless methods such as the Moving Least Square (MLS) collocation method. In this work, we propose an adaptive high-order numerical algorithm based on RPIM to simulate the thermoviscoplastic behavior of a material mixing observed in the Friction Stir Welding (FSW) process. The proposed adaptive meshfree RPIM algorithm adapts well to the geometric and physical data by choosing a good shape parameter with a good precision. Our numerical approach combines the RPIM and the Asymptotic Numerical Method (ANM). A numerical procedure is also proposed in this work to automatically determine an improved shape parameter for the RBFs. The efficiency of the proposed algorithm is analyzed in comparison with an iterative algorithm.

• Journal of Korea Multimedia Society
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• v.21 no.2
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• pp.181-187
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• 2018

Line-laser beams are used for depth measurement of welding beads along the circumference of a pipe. For this, first we project a line-laser beam on an rotating pipe and take a sequence of images of the beam projected on the pipe using a CCD camera. Second, the projected line laser beam in each image is detected, converted into a thin curve. Finally measure the distance between the thinned curve and an imaginary line. When a line-laser beam is projected to a rough metal surface such as arc welding beads, the beam is severely scattered. This severe scattering makes the thinned curve perturbed. In this paper, we propose a thinning method robust against scattering of line lasers. First, we extract a projected line laser beam region using an adaptive threshold. Second, we model a thinned curve with a spline curve with control points. Next, we adjust the control points to fit the curve to the projected line-laser beam. Finally, we take a weighted mean of thin curves on a sequence of image frames. Experiments shows that the proposed thinning method results in a thinning curve, which is smooth and fit to the projected line-laser beam with small error.

• Journal of Computational Design and Engineering
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• v.2 no.4
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• pp.248-252
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• 2015

Currently composite manufacturing process, such as linear friction welding plus NC machining, is the main method for the manufacturing and repairing of complex parts with integrated structure. Due to different datum position and inevitable distortion from different processes, it is important to ensure sufficient machining allowance for complex parts during the NC machining process. In this paper, a workpiece localization approach for machining allowance optimization of complex parts based on CMM inspection is developed. This technique concerns an alignment process to ensure sufficient stock allowance for the single parts as well as the whole integrated parts. The mathematical model of the constrained alignment is firstly established, and then the symmetric block solution strategy is proposed to solve the optimization model. Experiment result shows that the approach is appropriate and feasible to distribute the machining allowance for the single and whole parts for adaptive machining of complex parts.