A fuzzy logic system (FLS) with a new sliding window defuzzifier is proposed for structural damage detection using modal curvatures. Changes in the modal curvatures due to damage are fuzzified using Gaussian fuzzy sets and mapped to damage location and size using the FLS. The first four modal vectors obtained from finite element simulations of a cantilever beam are used for identifying the location and size of damage. Parametric studies show that modal curvatures can be used to accurately locate the damage; however, quantifying the size of damage is difficult. Tests with noisy simulated data show that the method detects damage very accurately at different noise levels and when some modal data are missing.
Chang, P.C. (2003). Review paper: health monitoring of civil infrastructure . Structural Health Monitoring, 2(3), 257-267.
2.
Auweraer, H.V. (2003) International research projects on structural health monitoring: an overview. Structural Health Monitoring, 2(4), 341-358.
3.
Montalvao, D. , Maia, N.M.M. and Ribeiro , A.M.R. (2006). A review of vibration-based structural health monitoring with special emphasis on composite materials. The Shock and Vibration Digest, 38(4), 295-324.
4.
Carden, E.P. and Fanning, P. (2004). Vibration based condition monitoring: a review. Structural Health Monitoring, 3(4), 355-377.
5.
Doebling, S.W. , Farrar, C.R. and Prime, M.B. (1998). A summary review of vibration based damage identification methods. Shock and Vibration Digest, 30(3), 91-105.
6.
Salawu, O.S. (1997). Detection of structural damage through changes in frequency: a review. engineering structures, 19(9), 718-723.
7.
Kim, J.T. , Ryu, Y.S., Cho, H.M. and Stubbs, N. (2003). Damage identification in beam-type structures: frequency-based method vs mode-shape-based method . Engineering Structures, 25(1), 57-67.
8.
Stubbs, N. and Kim, J.T. (1996). Damage localization in structures without baseline modal parameters. AIAA Journal, 34(8), 1649-1654.
9.
Chen, J. and Garba, J.A. (1988). On-orbit damage assessment for large space structures . AIAA Journal, 26(9), 1119-1126.
10.
Pandey, A.K. and Biswas, M. (1994). Damage detection in structures using changes in flexibility. Journal of Sound and Vibration, 169(1), 3-17.
11.
Farrar, C.R. and Jauregui, D.A. (1998). Comparative study of damage identification algorithm applied to a bridgeI. Experiment. Smart Mater. Struct., 7(5), 704-719.
12.
Pandey, A.K., Biswas, M. and Samman, M.M. (1991). Damage detection from changes in curvature mode shapes. Journal of Sound and Vibration, 145(2), 321-332.
13.
Wahab, M.M.A. and Roeck, G.D. (1999). Damage detection in bridges using modal curvatures: application to a real damage scenario. Journal of Sound and Vibration, 226(2), 217-235.
14.
Ratcliffe, C.P. and Bagaria, W.J. (1998). Vibration technique for locating delamination in a composite beam. AIAA Journal , 36(6), 1074-1077.
15.
Hamey, C.S. , Lestari, W., Qiao, P. and Song G. (2004). Experimental damage Identification of carbon/epoxy composite beams using curvature mode shapes. Structural Health Monitoring, 3(4), 333-353.
16.
Qiao, P.H., Lu, K., Lestari, W., Wang, J. (2007). Curvature mode shape-based damage detection in composite laminated plates. Composite Structures, 80(3), 409-428.
17.
Reddy, K.V. and Ganguli, R. (2007). Fourier analysis of mode shapes of damaged beams. Computers, Mechanics and Continua , 5(2), 79-98.
18.
Pawar, P.M. , Reddy, K.V. and Ganguli, R. (2007). Damage detection in beams using spatial fourier analysis and neural networks. Journal of Intelligent Material Systems and Structures, 18(4), 347-360.
19.
Liu, P.L. (1995). Identification and damage detection of trusses using modal data. Journal of Structural Engineering, 121(4), 599-608.
20.
Sawyer, J.P. and Rao, S.S. (2000). Structural damage detection and identification using fuzzy logic. AIAA Journal, 38(12), 2328-2335.
21.
Ganguli, R. (2001). A fuzzy logic system for ground based structural health monitoring of a helicopter rotor using modal data. Journal of Intelligent Material Systems and Structures , 12(6), 397-407.
22.
Pawar, P.M. and Ganguli, R. (2003). Genetic fuzzy system for damage detection in beams and helicopter rotor blades. Computer Methods in Applied Mechanics and Engineering, 192(16-18), 2031-2057.
23.
Zadeh, L. (1996). Fuzzy logic = computing with words. IEEE Transactions on Fuzzy Systems, 4(2), 103-111.
24.
Reddy, J.N. (2005). An Introduction to the Finite Element Method, New York: McGraw Hill, Inc.
25.
Roy, N. and Ganguli, R. (2005). Helicopter rotor blade frequency evolution with damage growth and signal processing, Journal of Sound and Vibration, 283(3-5), 821-851.
26.
Singh, K., Roy, N. and Ganguli, R. (2007). Monitoring low cycle fatigue damage in turbine blades using vibration characteristics, Mechanical Systems and Signal Processing, 21(1), 480-501.
27.
Bakhary, N. , Hao, H. and Deeks, A.J. (2007). Damage detection using artificial neural network with consideration of uncertainties, Engineering Structures29(11), 2806-2815.
28.
Jin, Y., Seelen, W.V. and Sendhoff, B. (2000). Extracting interpretable fuzzy rules from rbf neural networks. Ruhr-Universitat Bochum Institut fur Neuroinformatik 44780 Bochum, FRG, Report, IR-INI 2000-02, ISSN 0943-2752.
29.
Abe, S. and Lin, M.S. (1995). A method for fuzzy rules extraction directly from numerical data and its application to pattern recognition. IEEE Transactions on Fuzzy Systems, 3(1), 18-28.
30.
Chi, Z., Yan, H. and Pham, T. (1998). Fuzzy algorithms: With applications to image processing and pattern recognition, SingaporeWorld Scientific.
31.
Grabowskaa, J., Palaczb, M. and Krawczuka, M. (2008). Damage identification by wavelet analysis. Mechanical Systems and Signal Processing , 22(7), 1623-1635.
32.
Chen, H.G., Yan, Y.J., Chen, W.H., Jiang, J.S., Yu, L. and Wu., Z.Y. (2007). Early Damage Detection in Composite Wingbox Structures using Hilbert-Huang Transform and Genetic Algorithm. Structural Health Monitoring, 6(4), 281-297.
