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The following paper presents a pattern recognition approach to the condition monitoring of technical objects. The Noise-Assisted Feature Subset Evaluation (NAFSE) method addressed for the extraction of diagnostic parameters was used. The NBV-based classifier conducted the final recognition of the object’s condition on the basis of the diagnostic parameters obtained from the NAFSE method. The effectiveness of the proposed pattern recognition approach is illustrated by effective vibrodiagnostics of pre-stressed concrete structures. The approach shows potential for the damage detection of pre-stressed concrete structures at an early stage of damage development.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
33--42
Opis fizyczny
Bibliogr. 10 poz., il., rys., wykr.
Twórcy
autor
- Warsaw University of Technology, Institute of Vehicles
autor
- Warsaw University of Technology, Institute of Vehicles
Bibliografia
- 1. Dybała, J. (2009). Comparative analysis of support vector machine and nearest boundary vector classifier. In Reliability, Maintainability and Safety, 2009. ICRMS 2009. 8th International Conference on, pages 963–965. IEEE.
- 2. Dybała, J. (2013). Vibrodiagnostics of gearboxes using NBV-based classifier: A pattern recognition approach. Mechanical Systems and Signal Processing, 38(1):5–22.
- 3. Gałęzia, A., Gontarz, S., Jasiński, M., Mączak, J., Radkowski, S., and Seńko, J. (2012). Distributed system for monitoring of the large scale infrastructure structures based on analysis of changes of its static and dynamic properties. In Key Engineering Materials, volume 518, pages 106–118. Trans Tech Publ.
- 4. Gołaski, L., Świt, G., Kalicka, M., and Ono, K. (2005). Acoustic nondestructive techniques as a new method for evaluation of damages in prestressed concreto structures: failure of concrete structures. Journal of Acoustic Emission, 24:187–195.
- 5. Gontarz, S. and Radkowski, S. (2012). Impact of various factors on relationships between stress and eigen magnetic field in a steel specimen. IEEE Transactions on Magnetics, 48(3):1143–1154.
- 6. Hecht-Nielsen, R. (1987). Counter propagation networks. Applied Optics, 26(23):4979–4984.
- 7. Hecht-Nielsen, R. (1988). Applications of counter propagation networks. Neural Networks, 1(2):131–139.
- 8. Krause, M. and Wiggenhauser, H. (1997). Ultrasonic pulse echo technique for concreto elements using synthetic aperture. CSNDT JOURNAL, 19(3):7–12.
- 9. Radkowski, S. and Szczurowski, K. (2012). Use of vibroacoustic signals for diagnosis of prestressed structures. EKSPLOATACJA I NIEZAWODNOŚĆ, 14(1):82–88.
- 10. Sansalone, M. J. and Streett, W. B. (1997). Impact-echo: nondestructive evaluation of concrete and masonry.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-58f58c45-b1c9-42a0-bb02-b4ecbdc23dd3