Journal of Mechanical Design and Vibration
ISSN (Print): 2376-9564 ISSN (Online): 2376-9572 Website: Editor-in-chief: Shravan H. Gawande
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Journal of Mechanical Design and Vibration. 2013, 1(1), 1-4
DOI: 10.12691/jmdv-1-1-1
Open AccessArticle

Fault Diagnosis of Cracked Cantilever Composite Beam by Vibration Measurement and RBFNN

Irshad A Khan1, , Adik Yadao1 and Dayal R Parhi1

1Mechanical Engineering Department, NIT Rourkela, India

Pub. Date: January 15, 2014

Cite this paper:
Irshad A Khan, Adik Yadao and Dayal R Parhi. Fault Diagnosis of Cracked Cantilever Composite Beam by Vibration Measurement and RBFNN. Journal of Mechanical Design and Vibration. 2013; 1(1):1-4. doi: 10.12691/jmdv-1-1-1


In the current investigation numerical and radial basis function neural network (RBFNN) are adopted for diagnosis of fault in a cantilever composite beam structure present in form of transverse cracks. The presence of cracks a severe threat to the performance of structures and it affects the vibration signatures (Natural frequencies and mode shapes). The material used in this analysis is graphite fiber reinforced polyimide composite. The Numerical analysis is carried out by using commercially available software package ANSYS to find the relation between the change in natural frequencies and mode shapes for the cracked and un-cracked composite beam. Which subsequently used to the design of smart system based on RBFNN for forecast of crack depths and locations following inverse technique. The RBFNN controller is developed with relative natural frequencies and relative mode shapes difference as input parameters to calculate the deviation in the vibration parameters for the cracked dynamic structure. The output from the RBFNN controller is relative crack depth and relative crack location. Results from numerical analysis are comparing with experimental results having good agreement to the results predicted by the RBFNN controller.

crack natural frequencies Mode shapes RBFNN Ansys

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[1]  Kisa, M., “Free vibration analysis of a cantilever composite beam with multiple cracks,” Composites Science and Technology, vol. 64, pp. 1391-1402, 2004.
[2]  Krawczuk, M., and Ostachowicz, W. M., “Modelling and vibration analysis of a cantilever composite beam with a transverse open crack,” Journal of Sound and Vibration, vol. 183 (1), pp. 69-89, 2005.
[3]  Katunin, A., “Identification of multiple cracks in composite beams using discrete wavelet transform,” Scientific Problems of Machines Operation and Maintenance, vol. 2 (162), pp. 41-52, 2010.
[4]  HuN, WangX., FukunagaH, YaoZ.H., ZhangH. X., WuZ. S., “Damage Assessment of structures using test data,” International Journal of solids and structures, vol. 38, pp. 3111-3124, 2001.
[5]  SureshS, Omkar, S. N.,GanguliR., and ManiV., “Identification of crack location and depth in a cantilever Beam Using a Modular Neural Network Approach,” Smart Materials and Structures, vol. 13, pp. 907-916, 2004.
[6]  TianJ. LiZ., and SuX., “Crack detection in beams by wavelet analysis of transient flexural waves,” Journal of Sound and Vibration, vol. 261, pp. 715-727, 2003.
[7]  LoutridisaS., DoukabE., and HadjileontiadiscL.J., “Forced vibration behaviour and crack detection of cracked beams using instantaneous frequency,” NDT & E International, vol. 38 pp. 411-419, 2005.
[8]  MehrjooM., KhajiN., MoharramiH., andBahreininejadA., “Damage detection of truss bridge joints using Artificial Neural Networks,” Expert Systems with Applications, vol. 35, pp. 1122-1131, 2008.
[9]  AgostoF.J, SerranoD, ShafiqB, and CecchiniA, “Neural network based nondestructive evaluation of sandwich composites,” Composites: Part B, vol. 39, pp. 217-225, 2008.
[10]  SaravananN., Kumar SiddabattuniV.N.S., and RamachandranK.I., “Fault diagnosis of spur bevel gear box using artificial neural network (ANN), and proximal support vector machine (PSVM),” Applied Soft Computing, vol. 10, pp. 344-360, 2010.