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Elastic waves in structure tests. Part 1. Signal processing
Języki publikacji
Abstrakty
The paper presents an idea of elastic waves application in the field of structure test and health monitoring. Smart technology used for this purpose can lead further to autonomous systems that may operate in real time providing information about the structure state or even remaining operational life. However, the analysis of the elastic waves signals, assuming reflections from structure boundaries, connections, cracks, delaminations, etc., may be rather clear or pretty complex. Due to this fact advance signal processing techniques were used here for a purpose of signal de-noising and features extraction. The proposed system performs two levels of structure diagnosis: novelty detection and damage prediction. The developed procedure of signal processing has been studied for the elastic waves signals measured in various laboratory specimens. It has been proved that the application of those techniques improves the accuracy of the designed diagnosis system. Trained neural networks were able to detect damage and predict its size with reasonably well accuracy.
Rocznik
Tom
Strony
37--42
Opis fizyczny
Bibliogr. 12 poz., il.
Twórcy
Bibliografia
- [1] Kessler S.S., Spearing S.M., Soutis C., Damage detection in composite materials using Lamb wave methods, Smart Mater. Struct, 2002, 11, 269-278
- [2] Staszewski W.J., Lee B.C., Mallet L., Scarpa F., Structural health monitoring using laser vibrometry: I. Lamb wave sensing, Smart Mater. Struct., 2004, 13, 251-260
- [3] Mallet L., Lee B.C., Staszewski W.J., Scarpa F., Structural health monitoring using scanning laser vibrometry: II. Lamb waves for damage detection, Smart Mater. Struct., 2004, 13, 261-169
- [4] Giurgiutiu V., Tuned Lamb Wave Excitation and Detection with Piezoelectric Wafer Active Sensors for Structural Health Monitoring, Journal of intelligent material systems and structures, 2005, 16, 291-305
- [5] Ostachowicz W.M., Damage detection of structures using spectral finite element method, Computers and Structures, 2008, 86, 454-462
- [6] Nazarko P., Ziemiański L., Wykrywanie uszkodzeń konstrukcji z wykorzystaniem fal sprężystych oraz sztucznych sieci neuronowych, Zeszyty Naukowe Politechniki Rzeszowskiej, 2008, 258, 271-28
- [7] Nazarko P., Ocena stanu konstrukcji i wykrywanie uszkodzeń w jej elementach, Politechnika Rzeszowska, Rzeszów, 2008
- [8] Donoho D.L., De-noising by Soft-Thresholding, IEEE Transactions on Information Theory, 1995,41,613-627
- [9] Woo S., Goo N.S., Identification of failure mechanisms in a smart composite actuator with a thin sandwiched PZT plate based on waleform and primary frequency analyses, Smart Mater. Struct., 2007, 16, 1460-1470
- [10] Staszewski W., Boller C., Tomlinson G., Health Monitoring of Aerospace Structures: Smart Sensor Technologies and Signal Processing, John Wiley & Sons, 2003
- [11] Waszczyszyn Z., Ziemiański L., Neural networks in the identification analysis of structural mechanics problems, Parameter Identification of Materials and Structures, Springer - Wien, 2005, 265-340
- [12] Nazarko P., Jurek M., Ziemiański L., Fale sprężyste w badaniach konstrukcji: II. Badania laboratoryjne, Zeszyty Naukowe Politechniki Rzeszowskiej, 2009
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Bibliografia
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bwmeta1.element.baztech-article-BTB2-0058-0055