Sensor fusion using neural network in the robotic welding
K. Ohshima, M. Yabe, Kenzo Akita, K. Kugai, Takefumi Kubota, Satoshi Yamane
- 发表年份
- 2002
- 引用次数
- 9
摘要
It is important to realize intelligent welding robots to obtain a good quality of the welding results. For this purpose, it is required to detect the torch height, the torch attitude, the deviation from the center of the gap. In order to simultaneously detect those, the authors propose sensor fusion by using the neural network, i.e., the information concerning the welding torch is detected by using both the welding current and the welding voltage. First, the authors deal with the welding phenomena as the melting phenomena in the electrode wire of the MIG welding and the CO/sub 2/ short circuiting welding. Next, the training data of the neural networks are made from the numerical simulations. The neuro arc sensor is trained so as to get the desired performance of the sensor. By using it, the seam tracking is carried out in the T-joint.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002