DETECTION OF TRANSVERSE CRACKS IN A COMPOSITE BEAM USING COMBINED FEATURES OF LAMB WAVE AND VIBRATION TECHNIQUES IN ANN ENVIRONMENT

Publications

Share / Export Citation / Email / Print / Text size:

International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering, Engineering, Electrical & Electronic

GET ALERTS

eISSN: 1178-5608

DESCRIPTION

2
Reader(s)
7
Visit(s)
0
Comment(s)
0
Share(s)

VOLUME 1 , ISSUE 4 (December 2008) > List of articles

DETECTION OF TRANSVERSE CRACKS IN A COMPOSITE BEAM USING COMBINED FEATURES OF LAMB WAVE AND VIBRATION TECHNIQUES IN ANN ENVIRONMENT

Ramadas C. / Krishnan Balasubramaniam / M. Joshi / C.V. Krishnamurthy

Keywords : DETECTION OF TRANSVERSE CRACKS IN A COMPOSITE BEAM USING COMBINED FEATURES OF LAMB WAVE AND VIBRATION TECHNIQUES IN ANN ENVIRONMENT

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 1, Issue 4, Pages 970-984, DOI: https://doi.org/10.21307/ijssis-2017-331

License : (CC BY-NC-ND 4.0)

Published Online: 02-November-2017

ARTICLE

ABSTRACT

The detection, location and sizing of transverse cracks in a composite beam, by combining damage features of Lamb wave and vibration based techniques in artificial neural network (ANN) environment, using numerical finite element model, is discussed. Four damage features, time of flight (TOF) and amplitude ratio, which are Lamb wave based features and first and second natural frequencies, which are vibration based features were used as input to ANN. The output of ANN was crack location and depth. It was demonstrated that through the simultaneous employment of features from the two modalities in an ANN environment, the sizing could be done more effectively.

Content not available PDF Share

FIGURES & TABLES

REFERENCES

[1] Rose. J. L., Ultrasonic Waves in Solid Media, First edition, Cambridge University Press, 1999, pp. 101,
[2] Kim-Ho Ip, Yiu-Wing Mai, Delamination detection in smart composite beams using Lamb waves. Smart Mat. & Str 2004; 13: 544-551.
[3] Pandey A. K, Biswas. M, and Samman M. M, Damage detection from changes in curvature mode shapes. J. of Sound and Vibration 1991; 145(2): 321-332
[4] Yao G. C, Chang. K. C and Lee. G. C, Damage diagnosis of steel frames using vibrational signature analysis. J. of Engineering Mechanics 1992; 118(9): 153-170
[5] Shi. Z. Y, Law S. S and Zhang L. M, Structural damage localization from modal strain energy change, J. of Sound and Vibration 1998; 218(5): 825-844
[6] Cornwell. P, Doebling. S. W and Farrar. C. R, Application of the Strain energy damage detection method to plate like structures, J. of Sound and Vibration 1999; 224(2): 359-374
[7] Maeck. J and Roeck. G. D.E, Dynamic Bending and Torsion Stiffness Derivation from Modal Curvatures and Torsion Rate. J. of Sound and Vibration 1999; 255(1): 153-170.
[8] Su. Z and Ye. L, Lamb wave-based quantitative identification of delamination in CF/EP composite structures using artificial neural algorithm. Elsevier J. of Compos Struct 2004; 66: 627-637
[9] Kesavan. A, Deivasigamani. M, John. S, Herszberg. I, (2006), Damage detection in T – joint composite structures, Elsevier J. of Compos Struct 2004; (75): 313 – 320.
[10] Kudva, J, Munir. N, and P. Tan, Damage Detection in Smart Structures Using Neural Networks and Finite Element Analysis. Proc. of ADPA/AIAA/ASME/SPIE Conference on Active Materials and Adaptive Structures 1991, 559–562.
[11] Wu, X, Ghaboussi. J, and Garrett. J. H, Use of Neural Networks in Detection of Structural Damage. Computers and Structures 1992; 42(4): 649–659.
[12] Haykin. S, Neural Networks: A comprehensive foundation, Second edition, Pearson Prentice Hall publications. pp – 183-197.
[13] Demuth. H and Beale. M, Neural Network Toolbox User’s Guide Version 4, For Use with MATLAB. pp - 5.2-5.73.

EXTRA FILES

COMMENTS