Signals from several sensors were employed for real-time laser weld quality monitoring. Sheet-metal butt-joint laser welds of three quality classes (full penetration, partial penetration, gapped) were produced in experimental trials. Optical, air-born acoustic and plasma charge signals acquired during welding were subsequently Fourier-transformed and the spectra were analyzed individually to determine relationships to laser weld quality. The frequency bands most highly correlated to weld quality were identified by stepwise linear discriminant analysis (LDA) of the spectra. Testing of the quality discriminators formulated by LDA of the spectral data showed that the acoustic signal was most reliably correlated with weld quality. Fusing the data from all three sensors prior to LDA analysis produced a discriminator that had about the same reliability as one based on acoustic data alone.
Statistical Classification of Spectral Data for Laser Weld Quality Monitoring
Contributed by the Manufacturing Engineering Division for publication in the JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING. Manuscript received January 2000; revised August 2001. Associate Editor: S. Jack Hu.
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Ali, A., and Farson, D. (April 29, 2002). "Statistical Classification of Spectral Data for Laser Weld Quality Monitoring ." ASME. J. Manuf. Sci. Eng. May 2002; 124(2): 323–325. https://doi.org/10.1115/1.1455028
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