| Budget Amount *help |
¥3,500,000 (Direct Cost: ¥3,500,000)
Fiscal Year 2000: ¥1,300,000 (Direct Cost: ¥1,300,000)
Fiscal Year 1999: ¥2,200,000 (Direct Cost: ¥2,200,000)
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| Research Abstract |
In welding of steel plates, the welding parameters including groove shape, plate thickness, welding speed and so on change with elapse time. Accordingly, it is very important to select the optimum welding conditions by controlling them according to change of welding parameters. In order to realize the adaptive control of welding conditions, new control systems were constructed.
The first system used a CCD camera which was fixed at back side of welding torch, and it monitored the condition of the molten pool. In particular, the shape and dimension of the molten pool were measured during welding, and in-process control was performed to keep the shape and dimension. When the dimension of molten pool, such as pool width, increased, the control system decreased the welding current and keep the dimension of molten pool constant. In order to construct a robust control system, artificial neural network was applied to it. Furthermore, the system was applied to welding of fixed pipes, and effectiveness of the system was confirmed.
The second system has a monitoring system of oscillation of molten pool. Already, it is well known that the oscillation frequency of the molten pool changes with penetration. In this research, new oscillating processes including assist gas oscillating method, pulse shielding gas oscillating method and pulse back assist gas oscillating method were proposed, and characteristics of these oscillating methods were investigated. As a result, it is confirmed that the gas oscillating method can oscillate a molten pool with relatively small size. which is difficult to be oscillated by the conventional pulse current oscillating method. Furthermore, welding control experiments were performed using the system constructed in this study, and the effectiveness of the system in penetration control was verified.
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