A fuzzy pattern recognition based system for monitoring laser weld quality

摘要

In-process monitoring of welding has become important as the use of laser welding increases. Plasma and spatter are measured and used as signals for estimating the quality of a weld. The measurement system consists of three photodiode sensors (one IR and two UV) to detect the plasma and spatter signals in CO{sub}2 laser welding. The estimating algorithm was constructed using fuzzy pa(tern recognition considering the amplitudes as well as amounts of data beyond the tolerance boundary. Weld qualities were classified as optimal heat input, slightly low heat input, low heat input and misalignment of focus. Also, an algorithm for detecting spatter was created in order to find the partially produced pit. These algorithms were used for quality monitoring in tailored blank welds with a CO{sub}2 laser.