【摘 要】
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The neural network modeling of FCAW penetration is researched in this paper, molten pool image is acquired by CCD, and preweld gap is gotten from laser vision s
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The neural network modeling of FCAW penetration is researched in this paper, molten pool image is acquired by CCD, and preweld gap is gotten from laser vision system, the weld penetration is estimated according to the information include welding current, welding voltage, weld width, molten pool half length and gap width. The training samples of network can be partially gotten by numerical simulation. Single neuron self-tuning PID weld penetration controller is designed, and improved Hebb learning algorithm is applied for weights adjusting. Welding current is adjusted to make the weld penetration stable. The results of experiment with various cross-section and preweld gap workpiece show that this system is suitable to molten pool control.
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