Objective
Gas metal arc welding (GMAW) is one of the fundamental joining technologies. Technical progress in this field demands constant improvements in the technological properties of the welding consumables, e.g. flux-cored wires, and optimisation of the welding procedure. To control the quality of a welding product it is necessary to relate process monitoring and stochastical description of the process to mathematical and physical models.
This project is to develop an intelligent process monitoring system based on a mathematical, physical and stochastical model of the GMAW process. The model will be based on the probability densitiy distributions of the process signals of welding voltage and welding current and the class frequency distributions of time variables, e.g arc burning time and short-circuiting time. Furthermore, the model has to take into account the physical phenomena in the arc discharge. Fuzzy algorithms will be used for evaluating the results.
Welding experiments are necessary to correlate the process quality with the product quality. Quality assurance in production will be achieved if the process quality can be evaluated by statistical analysis of the significant process signals with respect to the product quality.
Topic(s)
Call for proposal
Data not availableFunding Scheme
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30167 Hannover
Germany