Politechnika Gdańska

 

Opis

In recent years, structural damage detection and health monitoring have been subjects of intensive investigation due to their practical importance. For important engineering structures the early detection of damage is essential since propagation of defects might lead to a catastrophic failure. A relatively recent area of research in damage identification is based on the wavelet analysis. This technique can be performed on mode shapes or static deflections of structure elements. An important feature of the wavelet transform is the ability to characterize the local irregularity introduced by damage into the displacement shape and to react to subtle changes of the structure response.  The aim of the research is to verify the applicability of the wavelet transform in damage localization in engineering structures.  The efficiency of the applied wavelets is verified by experimentally and analytically determined data. Beam, plate and shell structures are tested experimentally and compared with numerical solutions. The measurement of the beam displacements in a large number of spatially distributed points is obtained by the photogrammetric measurement technique, whereas the measurements of the beam, plate and shell mode shapes are obtained by the impulse dynamic testing.  The locations of defects indicated by a peak in the spatial variation of the transformed response are successfully determined. The application of artificial neural networks enables prediction of the crack locations even if the analyzed data are noisy and illegible.  The main advantage of the proposed damage detection technique is the effective identification of the defect position without knowledge of neither characteristics of structure nor its mathematical model. Spis treści: LIST OF SYMBOLS AND ABBREVIATIONS    1. INTRODUCTION   1.1. Damage detection in civil engineering structures  1.2. Wavelet transform application in damage detection  1.3. Aim and scope of study    2. WAVELET THEORY   2.1. Introduction to wavelet analysis  2.2. One-dimensional wavelet transform  2.2.1. Continuous wavelet transform  2.2.1.1. Vanishing moments  2.2.1.2. Detection of singularities  2.2.2. Discrete wavelet transform  2.2.2.1. Orthogonal wavelet transform  2.2.2.2. Biorthogonal wavelet transform  2.2.3. Examples of wavelets  2.3. Two-dimensional wavelet transform  2.3.1. Continuous wavelet transform  2.3.2. Discrete wavelet transform  2.3.2. l. Orthogonal wavelet transform  2.3.2.2. Biorthogonal wavelet transform  2.3.3. Examples of wavelets  2.4. Summary    3. WAVELET ANALYSIS IN DAMAGE DETECTION   3.1. Input signals  3.1.1. Experimental procedure for deflection lines determination  3.1.2. Experimental procedure for mode shapes determination  3.2. Wavelet selection for damage detection  3.2.1. One-dimensional wavelets  3.2.2. Two-dimensional wavelets  3.3. Discrete and continuous wavelet transform in damage detection  3.3.1. One-dimensional wavelet transform  3.3.2. Two-dimensional wavelet transform  3.4. Boundary effects  3.4.1. One-dimensional wavelet transform  3.4.2. Two-dimensional wavelet transform  3.5. Summary and conclusions    4. DAMAGE DETECTION ON EXPERIMENTAL EXAMPLES   4.1. Beam - static deflection lines  4.1.1. Experimental investigations of beam deflection lines  4.1.2. Numerical simulations  4.1.3. Results of wavelet analysis  4.2. Beam - mode shapes  4.2.1. Experimental investigations of beam mode shapes  4.2.2. Numerical simulations  4.2.3. Results of wavelet analysis  4.3. Plate - mode shapes  4.3.1. Experimental investigations of plate mode shapes  4.3.2. Numerical simulations  4.3.3. Results of wavelet analysis  4.4. Cylindrical shell - mode shapes  4.4.1. Experimental investigations of cylindrical shell mode shapes  4.4.2. Numerical simulations  4.4.3. Results of wavelet analysis  4.5. Summary and conclusions    5. DAMAGE DETECTION SYSTEMS BASED ON NEURAL NETWORKS   5.1. Fundamentals  5.2. Damage assessment using neural networks  5.3. Backpropagation neural network  5.4. Neural network defect detection system  5.4.1. Architecture  5.4.2. Training  5.4.3. Results of testing on experimental beam deflection lines  5.4.4. Results of testing on experimental beam mode shapes  5.4.5. Results of testing on experimental plate mode shapes  5.4.6. Results of testing on experimental shell mode shapes  5.5. Summary and conclusions 6. FINAL REMARKS 6.1. General remarks 6.2. Original elements of the study ACKNOWLEDGEMENTS  REFERENCES SUMMARY IN ENGLISH SUMMARY IN POLISH

Dane techniczne

Autor	Rucka Magdalena, Wilde Krzysztof
Język	angielski
Rok wydania	2007
Format	B5
Okładka	miękka
Ilość stron	117

Sklepy z Application of wavelet analysis in damage detection and localization

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