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2011 | 119 | 6A | 946-949
Article title

Neural Classifiers of Vibroacoustic Signals in Implementation on Programmable Devices (FPGA) - Comparison

Content
Title variants
Languages of publication
EN
Abstracts
EN
The research includes comparative analysis of the effect of the recording of weight vectors and input data of selected neural classifiers with fixed-point numbers. Research has been conducted due to insufficient literature on the influence of such a recording on the correct classification of vibroacoustic signals by neural networks. This current issue was brought up in authors' earlier researches, concerning realization of neural classifiers on programmable logical devices field programmable gate array, with the application of fixed-point processor. During the analysis, three types of neural classifiers were compared in the tests: classifier based on neural network - length vector quantization, classifier using radial neural networks - radial basis functions, and third - counter propagation neural network. The problem stated was to recognize technical state of gear transmission DMA-1 in variable operating conditions. Vectors, based on estimates derived from processed vibroacoustic signals were used as teaching material.
Keywords
EN
Year
Volume
119
Issue
6A
Pages
946-949
Physical description
Dates
published
2011-06
References
  • 1. C. Cempel, Vibroacoustics Diagnostics, Państwowe Wydawnictwo Naukowe, Warszawa 1989, p. 23 (in Polish)
  • 2. W. Cioch, Machine Dynamics Problems 27, 57 (2003)
  • 3. S. Osowski, Neural Networks for Computing, Oficyna Wydawnicza Politechniki Warszawskiej, Warszawa 2000, p. 37 (in Polish)
  • 4. R. Tadeusiewicz, Neural Networks, Akademicka Oficyna Wydaw. RM, Warszawa 1993, p. 65 (in Polish)
  • 5. J. Majewski, P. Zbysiński, FPGA Devices in Examples, 1st ed., Wydawnictwo BTC, Warszawa 2007, p. 7 (in Polish)
  • 6. K. Skahill, Projecting of Programmable Logic Devices, 2nd ed., Wydawnictwo Naukowo-Techniczne, Warszawa 2004, p. 20 (in Polish)
  • 7. B. Łazarz, G. Wojnar, P. Czech, in: Maintenance Reliability 49, 68 (2011)
  • 8. B. Łazarz, P. Czech, A. Wilk, in: Second World Congress on Engineering Asset Management and the Fourth Int. Conf. on Condition Monitoring 'WCEAM CM 2007', Harrogate (UK) 2007, p. 1190
  • 9. B. Łazarz, G. Wojnar, H. Madej, P. Czech, Mechanika (Lituania) 80, 56 (2009)
  • 10. H. Sarimveis, P. Doganis, A. Alexandridis, Adv. Eng. Software 37, 218 (2006)
  • 11. J. Adamczyk, W. Cioch, P. Krzyworzeka, Zagadnienia Eksploatacji Maszyn 34, 373 (1999)
  • 12. B. Samanta, Eng. Appl. Artificial Intellig. 16, 657 (2003)
  • 13. J. Żurada, M. Barski, W. Jędruch, Artificial Neural Networks, Wydawnictwo Naukowe PWN, Warszawa, 1996, p. 240 (in Polish)
  • 14. G.P. Zhang, IEEE Appl. Rev. 30, 451 (2000)
  • 15. T. Kohonen, Neurocomputing 21, 1 (1998)
  • 16. T. Masters, Neural Networks in Practice, Wydawnictwo Naukowo-Techniczne, Warszawa 1996, p. 15 (in Polish)
Document Type
Publication order reference
YADDA identifier
bwmeta1.element.bwnjournal-article-appv119n6a09kz
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