Monitoring fault condition during manufacturing using the Karhunen-Loève transform

Proceedings of the ASME Design Engineering Technical Conference

Volumn 1D-1997, Issue , 1997, Pages

  Tumer, Irem Y ^a   Wood, Kristin L ^a   Busch Vishniac, Ilene J ^a  

^a The University of Texas at Austin   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EIGENVALUES AND EIGENFUNCTIONS; MANUFACTURE; SIGNAL PROCESSING; STOCHASTIC SYSTEMS; VIBRATIONS (MECHANICAL);

COEFFICIENT VECTOR; FAULT CONDITIONS; FAULT PATTERNS; GENERAL FUNCTIONS; MATHEMATICAL FOUNDATIONS; MEASURED SIGNALS; NONSTATIONARY; PHYSICAL SIGNIFICANCE;

CONDITION MONITORING;

EID: 85030038125     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1115/DETC97/VIB-4234     Document Type: Conference Paper

References (31)

1. Ahmed, N. and Rao, K., 1975. Orthogonal Transforms for Digital Signal Processing. Springer-Verlag, New York.
2. Akansu, A. and Haddad, R., 1992. Multiresolution Signal Decomposition: Transforms, Subbands, Wavelets. Academic Press, Inc., San Diego, Ca.
3. Algazi, V. R., Brown, K. L., and Ready, M. J., 1993. Transform representation of the spectra of acoustic speech segments with applications, Part I: General approach and application to speech recognition. IEEE Transactions on Speech and Audio Processing, 1(2):180-195.
4. Ball, K., Sirovich, L., and Keefe, L., 1991. Dynamical eigenfunction decomposition of turbulent channel flow. International Journal for Numerical Methods in Fluids, 12:585-604.
5. Barker, R., Klutke, G., and Hinich, M., 1993. Monitoring rotating tool wear using higher-order spectral features. Journal of Engineering for Industry, 115:23-29.
6. Bendat, J. S. and Piersol, A. G., 1986. Random Data: Analysis and Measurement Procedures. John Wiley & Sons, New York, NY.
7. Berry, J. E., 1991. How to track rolling element bearing health with vibration signature analysis. Sound and Vibration, pages 24-35.
8. Boashash, B., editor, 1992. Time-Frequency Signal Analysis Methods and Applications. John Wiley & Sons, New York.
9. Box, G., Jenkins, G., and Reinsel, G., 1994. Time Series Analysis: Forecasting and Control. Prentice Hall, New Jersey.
10. Braun, S., 1986. Mechanical Signature Analysis: Theory and Applications. Academic Press, London.
11. Eppinger, S. D., Huber, C. D., and Pham, V. H., 1995. A methodology for manufacturing process signature analysis. Journal of Manufacturing Systems, 14(1):20-34.
12. Fackrell, J., White, P., and Hammond, J., 1994. Bispectral analysis of periodic signals in noise: theory, interpretation, and condition monitoring. In EUSIPCO'94, Edinburgh, UK.
13. Fukunaga, K., 1972. Introduction to Statistical Pattern Recognition. Academic Press, New York, NY.
14. Geng, Z. and Qu, L., 1994. Vibrational diagnosis of machine parts using the wavelet packet technique. British Journal of Non-Destructive Testing, 36(1):11-15.
15. Graham, M. D., Lane, S. L., and Luss, D., 1993. Proper orthogonal decomposition analysis of spatiotemporal temperature patterns. Journal of Physical Chemistry, 97(4):889-894.
16. Jones, R. M., 1994. A guide to the interpretation of machinery vibration measurements, Part I. Sound and Vibration, pages 24-35.
17. Kozek, W., 1993. Matched generalized gabor expansion of nonstationary processes. In The Twenty Seventh Asilomar Conference on Signals, Systems, & Computers, volume 1, pages 499-503.
18. Ladd, M. D., 1995. Detection of Machinery Faults in Noise Using Wavelet Transform Techniques. PhD thesis, The University of Texas, Austin, Tx.
19. Rioul, O. and Vetterli, M., 1991. Wavelets and signal processing. IEEE Signal Processing Magazine, pages 14-38.
20. Rohrbaugh, R. A., 1993. Application of time-frequency analysis to machinery condition assessment. In The twenty-seventh Asilomar Conference on Signals, Systems, & Computers, volume 2, pages 1455-1458.
21. Sirovich, L. and Keefe, L., 1987. Low-dimensional procedure for the characterization of human faces. Journal of the Optical Society of America, 4(3):519-524.
22. Sottile, J. and Holloway, L. E., 1994. An overview of fault monitoring and diagnosis in mining equipment. IEEE Transactions on Industry Applications, 30(5):1326-1332.
23. Spiewak, S., 1991. A predictive monitoring and diagnosis system for manufacturing. Annals of the CIRP: manufacturing technology, 40(1):401-404.
24. Therrien, C., 1992. Discrete Random Signals and Statistical Signal Processing. Prentice Hall, Englewood Cliffs, NJ.
25. Tumer, I., Srinivasan, R., and Wood, K., 1995. Investigation of characteristic measures for the analysis and synthesis of precision-machined surfaces. Journal of Manufacturing Systems, 14(5):378-392.
26. Tumer, I., Thompson, D., Wood, K., and Crawford, R., 1997a. Characterization of surface fault patterns with application to a layered manufacturing process. Accepted for publication in the Journal of Manufacturing Systems.
27. Tumer, I., Wood, K., and Busch-Vishniac, I., 1997b. Improving manufacturing precision using the Karhunen-Loève transform. In 1997 ASME Design for Manufactur-ing Conference, Integrated Design Symposium, Sacramento, California.
28. Whitehouse, D., 1994. Handbook of Surface Metrology. Institute of Physics Publishing, Bristol, UK.
29. Whitehouse, D. and Zheng, K., 1992. The use of dual space-frequency functions in machine tool monitoring. Measurement Science and Technology, 3:796-808.
30. Zahorian, S. A. and Rothenberg, M., 1981. Principal-components analysis for low-redundancy encoding of speech spectra. Journal of the Acoustical Society of America, 69(3):519-524.
31. Zhang, J., Martin, E., and Morris, J., June 1995. Fault detection and classification through multivariate statistical techniques. In Proceedings of the American Control Conference, pages 751-755, Seattle, Washington.