Self-Adjusting Welding Based on Thermal Data Weld Pool A
new kind of welding system that solves quality and productivity problems related to automated and mechanized welding is being developed at Loppeen-
ranta University of Technology (LUT; Finland). The system is self-adjusting, flexible, and adaptable such that it can be integrated as part of different robotic systems and different manufacturer’s power suppliers. Its self-adjust- ing properties are based on a new kind of sensor system which is controlled by a neural network program. Most often in welding a monitoring sensor is used which tracks the bevel angle, an essential part of the welding process. In the system being developed by LUT, there are also monitoring sensors for the thermal profile (the weld pool’s heat values) and the weld form. Data are transferred from sensors to the neural network which is able to deduce and react to simultaneous changes in mul- tiple variables. “When a mistake is detected, the system
them to run a robot. With the KUKA robot control, the user can take welders and make them into robot programmers, creating a higher technical capability job and giving them a path for growth in the company. Welders are embracing it and management loves the better productivity, quality, and of course, the ROI,” said Howell. Programming a robot involves teach and play back by physically driving the robot from point to point, using either plus or minus keys or a joystick in the case of the KRC4 con- troller, making selections from drop-down boxes and entering commands at each point. “The operator doesn’t have to memorize any code and our welder can hold 255 programs that can be recalled to consistently weld a wide mix of parts,” said Howell. The KUKA robot with the ESAB Aristo welding machine also has the ability to make a data set where all of the welding information including travel speed and weaving parameters are all in the same file. This means that cloning one good weld to another on a part or to another part or to another plant is easy with the ESAB/KUKA combination. One thing to remember, however, said Howell, “Robot consistency is both a good thing and potentially a bad thing. If you program wrong, it’ll run every part wrong, producing bad parts. If programmed right to weld specifications, you’re going to have consistently good quality every time. KUKA publishes data on path accuracy which is the most important consideration in arc welding to ensure getting the optimum weld width every time and avoiding wasting wire.”
is able both to correct it during the welding process and also calculate what other faults may arise. Thus the final product is flawless. “The problem with welding automation systems is that certain values are set for the work, based on which the whole weld is carried out, and only then is it checked whether the result is good. Now the welding is monitored throughout the whole process,” said Project Manager Markku Pirinen. “In the gas-shielded arc welding process, factors affecting outcome quality include the welding current, the arc voltage, the wire feeding and transporting speeds, and the position of the welding gun. With the help of the neural network, a regulating window can be set for these system variables, and they can then be controlled so that they remain within certain limits, which ensures that final product is as required.” Source:
www.sciencedaily.com March 20, 2015
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October 2015 |
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