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TECHNICAL PAPERS

Statistical Classification of Spectral Data for Laser Weld Quality Monitoring

[+] Author and Article Information
Afsar Ali

Mechanical Engineering and Engineering Mechanics, University of Michigan, Ann Arbor, MI 48109

Dave Farson

Welding Engineering, The Ohio State University, Columbus, OH 43210

J. Manuf. Sci. Eng 124(2), 323-325 (Apr 29, 2002) (3 pages) doi:10.1115/1.1455028 History: Received January 01, 2000; Revised August 01, 2001; Online April 29, 2002
Copyright © 2002 by ASME
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References

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Farson,  D., 2000, “Progress in Real-Time Laser Process Monitoring: Theory and Practice,” Sci. Technol. Weld. Joining, 5, pp. 194–201.
Sun,  A., Kannatey-Asibu,  E., and Gartner,  M., 1999, “Sensor Systems for Real-Time Monitoring of Laser Weld Quality,” J. Laser Appl., 11, pp. 153–168.
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Farson, D., and Kern, K., 1991, “Neural Network Classification of Laser Welds From Acoustical Signals.” Proceedings ICALEO’90, Orlando, FL, pp. 35–42.
Beyer, E., Maischner, D., and Kratzsch, Ch., 1995, “A Neural Network to Analyze Plasma Fluctuations with the Aim to Determine the Degree of full Penetration in Laser Welding,” Proceedings ICALEO’94, Laser Institute of America, Orlando, FL, pp. 51–57.
Ali, A., 1999, “In-Process Quality Monitoring of Laser Welds Using Multi-Sensor Measurements,” Ph.D. Thesis, The Ohio State University, Columbus, OH.
Johnson, R. A., and Wichern, D. W., 1992, Applied Multivariate Statistical Analysis, Prentice Hall, Englewood Cliffs, N.J.
SAS®/STAT User’s Guide, Ver. 6, 4th Ed., 1990, SAS Institute Inc. Cary, NC.
Murray,  G., 1977, “A Cautionary Note on Selection of Variables in Discriminant Analysis,” Appl. Stat., 26, No. 3, pp. 246–250.
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Brooks, I., and Iyengar, S., 1998, Multisensor Fusion, Prentice-Hall, Englewood Cliffs, N.J.

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