Resistance spot welding is an important and widely used method for joining metal objects. In this paper, various classification methods for identifying welding processes are evaluated. Using process identification, a similar process for a new welding experiment can be found among the previously run processes, and the process parameters leading to high-quality welding joints can be applied. With this approach, good welding results can be obtained right from the beginning, and the time needed for the set-up of a new process can be substantially reduced. In addition, previous quality control methods can also be used for the new process. Different classifiers are tested with several data sets consisting of statistical and geometrical features extracted from current and voltage signals recorded during welding. The best feature set - classifier combination for the data used in this study is selected. Finally, it is concluded that welding processes can be identified almost perfectly by certain features. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Haapalainen, E., Laurinen, P., Junno, H., Tuovinen, L., & Röning, J. (2005). Methods for classifying spot welding processes: A comparative study of performance. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3533 LNAI, pp. 412–421). Springer Verlag. https://doi.org/10.1007/11504894_58
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