Detection in a Robotised Short Circuting GMA Welding using Neural Networks
|Document type:||Conference Papers|
|Author(s):||Linus Pettersson, Stefan Adolfsson, Gunnar Bolmsjö, Ingvar Claesson|
|Title:||Detection in a Robotised Short Circuting GMA Welding using Neural Networks|
|Conference name:||IEEE International Symposium on Intelligent Signal Processing and Communication System|
|Organization:||Blekinge Institute of Technology|
|Department:||Department of Telecommunications and Signal Processing (Institutionen för telekommunikation och signalbehandling)
Department of Telecommunications and Signal Processing S-372 25 Ronneby
+46 455 38 50 00
|Abstract:||Today it is both time and cost consuming to check the quality of a weld when it is done off-line by an experienced weld operator. Therefor the need for an automatic detection is urgent in order to reduce production costs. There are systems for monitoring the quality of a weld commercially available but there is still some research that has to be done in this area in order to increase the reliability.
The method presented in this paper is neural network based and considers short circuiting GMA welding, but there is no obstacle for this solution to work on other types of robotised welding. By presenting the weld voltage to a neural network, the network is able to detect defects in the weld joint.
Testresults have shown that the detection rate is 100 percent and false alarms are nonexisting.
|Subject:||Signal Processing\Detection and Classification|