Wykrywanie uszkodzeń konstrukcji z wykorzystaniem fal sprężystych oraz sztucznych sieci neuronowych

• Autorzy: Nazarko P. , Ziemiański L.
• Konferencja: Problemy dynamiki konstrukcji / XIII Sympozjum Dynamiki Konstrukcji (XIII ; 25-27 września 2008 ; Rzeszów-Bystre, Polska)
• Języki publikacji: PL

Abstrakty

EN

Examination of structures integrity and failures detection are nowadays of great interest for both civil infrastructure and industry systems. This paper presents Structural Health Monitoring (SHM) technique that was tested on several laboratory models and utilizes elastic wave propagation phenomenon. Furthermore, it describes signals feature extraction procedure by using Principal Component Analysis (PCA). Artificial Neural Networks (ANNs) and statistical learning theory are used to determine and classify structure's damages. The results show that data reduction using PCA, followed by implementation of ANNs patterns recognition, provide a good indication of failure occurrence and they may be used for SHM.

Słowa kluczowe

PL

dynamika konstrukcji; drgania; SHM; fala sprężysta; uszkodzenie konstrukcji

EN

construction dynamics; vibration; SHM; elastic wave; structure damage

• Wydawca: Oficyna Wydawnicza Politechniki Rzeszowskiej
• Czasopismo: Zeszyty Naukowe Politechniki Rzeszowskiej. Mechanika
• Rocznik: 2008
• Tom: z. 74 [258]
• Strony: 271--282
• Opis fizyczny: Bibliogr. 9 poz., rys., tab., wykr.

Twórcy

autor

Nazarko P.

autor

Ziemiański L.

• Katedra Mechaniki Konstrukcji, Politechnika Rzeszowska, ul. W. Pola 2, 35-959 Rzeszów,

Bibliografia

• [1] M.R. Hernandez-Garcia, M. Sanchez-Silva, Learning Machines for Structural Damage Detection. N.D. Lagaros, Y. Tsompanakis eds. Intelligent Computational Paradigms in Earthquake Engineering, 158-187, 2007.
• [2] K. Worden, J.M. Dulieu-Barton, An Overview of Intelligent Fault Detection in Systems and Structures, Structural Health Monitoring, 3, 85-98, 2004.
• [3] Z. Waszczyszyn, L. Ziemiański, Parameter Identification of Materials and Structures, CISM Courses and Lectures, 469, 256-340, 2005.
• [4] S. Osowski, Sieci neuronowe w ujęciu algorytmicznym, WNT, Warszawa 1996.
• [5] W. Staszewski, C. Boiler, G. Tomlinson, Health Monitoring of Aerospace. Structures, John Wiley & Sons, 2004.
• [6] K. Kuźniar, Z. Waszczyszyn, Neural Networks and Principal Component Anafysis for Identification of Building Natural Periods, J. Comp. in Civ. Engrg., 20 (6), 431-436. 2006.
• [7] V. Giurgiutiu, Tuned Lamb Wave Excitation and Detection with Piezoelectric Wafer Active Sensors for Structural Health Monitoring, Journal of intelligent material systems and structures; 16, 291-305, 2005.
• [8] B.C. Lee, W. Staszewski, Lamb wave propagation modelling for damage detection; II. Damage monitoring strategy, Smart Material Structures, 16, 260-274, 2007.
• [9] P. Nazarko, L. Ziemiański, Application of neural networks and structural wave propagation phenomenon to quantitative damage evaluation. Computational Methods in Structural Dynamics and Earthquake Engineering, Rethymno, Crete. Greece, June 13-16, 2007.