Mobile welding robot system based on rotating arc sensor applied for large fillet welding seam tracking

Author(s):  
Zhi-wei Mao ◽  
Ji-luan Pan ◽  
Hua Zhang
Author(s):  
Jian Le ◽  
Hua Zhang ◽  
Ze Chai ◽  
Yinshui He ◽  
Xiaoqi Chen

The welding robot system designed in this paper is helpful to realize welding automation. The closed loop control system and algorithm of arc rotating speed have been designed, so arc rotating speed was stabilized near the set value and the tracking accuracy of fillet weld has been improved by the rotating arc sensor. A data acquisition system and a motion control system have been designed based on multi-sensor technology. The mapping relationship between the features in the welding seam image and the pose of the welding gun was established, so as to realize the identification of the pose of the welding gun based on three-wire laser vision sensing technology. The effect of wire extension, welding currents and welding voltages on the current waveform was investigated based on the rotating arc sensor. By using the designed system and algorithm, the welding deviations recognition experiment, the arc rotating speed control experiment and the tracking experiment of the right-angle welding seam have been carried out. The experimental results showed that the welding deviations were located within [Formula: see text][Formula: see text]mm, and the welding robot can track the complex welding seam accurately and reliably.


2012 ◽  
Vol 26 (4) ◽  
Author(s):  
Nguyễn Thành Luân ◽  
Trần Thiện Phúc ◽  
Nguyễn Duy Anh ◽  
Nguyễn Tân Tiến

2018 ◽  
Vol 21 (6) ◽  
pp. 1407-1412
Author(s):  
Jian-Hui Du ◽  
Jian-Xin Deng ◽  
Ke-Jian Huang ◽  
Jie-Sheng Huang ◽  
Xie Lei

Author(s):  
Chao Liu ◽  
Hui Wang ◽  
Yu Huang ◽  
Youmin Rong ◽  
Jie Meng ◽  
...  

Abstract Mobile welding robot with adaptive seam tracking ability can greatly improve the welding efficiency and quality, which has been extensively studied. To further improve the automation in multiple station welding, a novel intelligent mobile welding robot consists of a four-wheeled mobile platform and a collaborative manipulator is developed. Under the support of simultaneous localization and mapping (SLAM) technology, the robot is capable of automatically navigating to different stations to perform welding operation. To automatically detect the welding seam, a composite sensor system including an RGB-D camera and a laser vision sensor is creatively applied. Based on the sensor system, the multi-layer sensing strategy is performed to ensure the welding seam can be detected and tracked with high precision. By applying hybrid filter to the RGB-D camera measurement, the initial welding seam could be effectively extracted. Then a novel welding start point detection method is proposed. Meanwhile, to guarantee the tracking quality, a robust welding seam tracking algorithm based on laser vision sensor is presented to eliminate the tracking discrepancy caused by the platform parking error, through which the tracking trajectory can be corrected in real-time. The experimental results show that the robot can autonomously detect and track the welding seam effectively in different station. Also, the multiple station welding efficiency can be improved and quality can also be guaranteed.


2012 ◽  
Vol 548 ◽  
pp. 555-559
Author(s):  
Jian Ping Jia ◽  
Yun Long Liu ◽  
Jian Ping Chen ◽  
Ya Qin Zhang

Aimed at the situation that the welding voltage is easy to be disturbed by the voice outside, median filtering and average filtering are adopted to filtering signal of the voltage the rotating arc sensor collected in this paper. They can make the voltage waveform get obvious improvement. In order to get information which the welding torch deviated the welding seam more accurately, left and right integration, Characteristic Harmonics method and welding torch deviation recognition algorithm are adopted to identify the deviations in this paper. Finally compare the two kinds of identification deviation methods and obtain better welding torch deviated information.


Sign in / Sign up

Export Citation Format

Share Document