Sensor fusion using neural network in the robotic welding
- Saitama Univ., Urawa, Saitama (Japan)
- Himeji Inst. of Tech., Himeji, Hyougo (Japan)
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 the 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 neutral 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.
- OSTI ID:
- 415563
- Report Number(s):
- CONF-9510203--
- Country of Publication:
- United States
- Language:
- English
Similar Records
Weld penetration control in robotic GTAW using an infrared sensor
Prediction of Weld Penetration in FCAW of HSLA steel using Artificial Neural Networks