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Decomposition Of The Symptom Observation Matrix And Grey Forecasting In Vibration Condition Monitoring Of Machines Cover

Decomposition Of The Symptom Observation Matrix And Grey Forecasting In Vibration Condition Monitoring Of Machines

By: Czesław Cempel  
Open Access
|Dec 2008

References

  1. Bartelmus W., Zimroz Z. and Batra H. (2003). Gearbox vibration signal preprocessing and input values choice for neural network training, Proceedings of the Conference on AI Methods, Gliwice, Poland.
  2. Cempel C. (1999). Innovative developments in systems condition monitoring, Keynote Lecture, Proceedings of the Conference on Damage Assessment DAMAS'99, Dublin, Ireland, pp. 172-188.
  3. Cempel C., Natke H. G. and Yao J. P. T. (2000). Symptom reliability and hazard for systems condition monitoring, Mechanical Systems and Signal Processing 14(3): 495-505.10.1006/mssp.1999.1246
  4. Cempel C. (2003). Multidimensional condition monitoring of mechanical systems in operation, Mechanical Systems and Signal Processing 17(6): 1291-1303.10.1006/mssp.2002.1573
  5. Cempel C. and Tabaszewski M. (2007). Multidimensional vibration condition monitoring of nonstationary systems in operation, Mechanical Systems and Signal Processing 21(3): 1233-1241.10.1016/j.ymssp.2006.04.001
  6. Cempel C., Krakowiak M. (2006a). Influence of running stability and randomness of observation on the condition assessment in multidimensional machine diagnostics, Diagnostyka 40(4): 19-25.
  7. Cempel C. and Tabaszewski M. (2006b). Averaging the symptoms in multidimensional condition monitoring for machines in nonstationary operation, Proceedings of the 13 International Congress on Sound and Vibration, Vienna, Austria, CD-ROM.
  8. Cempel C. (2004). Implementing multidimensional inference capability in vibration condition monitoring, Proceedings of the Conference on Acoustical and Vibratory Surveillance, Senlis, France.
  9. Cempel C. (2005). Multi fault vibrational diagnostics of critical machines, Zagadnienia Eksploatacji Maszyn 4(144): 133-142.
  10. Cempel C. (1991). Vibroacoustic Condition Monitoring, Ellis Horwood, London.
  11. Cempel C. (1987). Simple condition forecasting techniques in vibroacoustical diagnostics, Mechanical Systems and Signal Processing 1(1): 75-82.10.1016/0888-3270(87)90084-7
  12. Cempel C. (2008). Forecasting the global and partial system condition by means of multidimensional condition monitoring, Journal of Theoretical and Applied Mechanics 46(4): 777-797.
  13. Deng J. L. (1982). Control problems of grey systems, Systems and Control Letters 1(5): 288-294.10.1016/S0167-6911(82)80025-X
  14. Deng J-L. (1989). Introduction to grey system theory, The Journal of Grey Systems 1(1): 1-24.
  15. Dunham M. H. (2003). Data Mining—Introductory and Advanced Topics, Prentice Hall, Englewood Cliffs, NJ.
  16. Golub G. H., VanLoan C. F. (1983), Matrix Computation, North Oxford Academic, Oxford.
  17. Jasiński M. (2004). Empirical models in gearbox diagnostics, Ph.D. thesis, Warsaw University of Technology, (in Polish).
  18. Korbicz J., Koscielny J. M., Kowalczuk Z. and Cholewa W. (Eds.) (2004). Fault Diagnosis—Models, Artificial Intelligence, Applications, Springer Verlag, Berlin.10.1007/978-3-642-18615-8
  19. Kiełbasiński A. and Schwietlick H. (1992). Numeric Linear Algebra, WNT, Warsaw, (in Polish).
  20. Natke H. G. and Cempel C. (2002). The symptom observation matrix for monitoring and diagnosis, Journal of Sound and Vibration 248(4): 597-620.10.1006/jsvi.2001.3800
  21. Natke H. G. and Cempel C. (1997). Model Aided Diagnosis of Mechanical Systems, Springer-Verlag, Berlin.10.1007/978-3-642-60413-3
  22. Pantopian N. H. and Larsen J. (1999). Unsupervised condition detection in large diesel engines, Proceedings of the IEEE Workshop on Neural Networks.
  23. Tabaszewski M. (2006). Forecasting of residual life of a fan mill by means of neural nets, Diagnostyka 3(39): 149-156, (in Polish).
  24. Tumer I. Y. and Huff E. M. (2002). Principal component analysis of tri-axial vibration data from helicopter transmission, Proceedings of 56th Meeting of the Society of Machine Failure Prevention Technology.
  25. Wen K. L. and Chang T. C. (2005). The research and development of completed GM(1,1) model toolbox using Matlab, International Journal of Computational Cognition 3(3): 42-48.
  26. Will T. (2005). Hanger matrix, two-thirds theorem, available at: http://www.uwlax.edu/faculty/will/svd/svd/index.html
  27. Żółtowski B. and Cempel C. (Eds.) (2004). Engineering of Machine Diagnostics, ITE Press, Radom, p. 1308, (in Polish).
  28. Yao A. W. L. and Chi S. C. (2004). Analysis and design of a Taguchi-Grey based electricity demand predictor for energy management systems, Energy Conversion and Management 45: 1205-1217.10.1016/j.enconman.2003.08.008
DOI: https://doi.org/10.2478/v10006-008-0050-7 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
Language: English
Page range: 569 - 580
Published on: Dec 30, 2008
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2008 Czesław Cempel, published by University of Zielona Góra
This work is licensed under the Creative Commons License.

Volume 18 (2008): Issue 4 (December 2008)