DOUBLE CRACKS IDENTIFICATION IN FUNCTIONALLY GRADED BEAMS USING ARTIFICIAL NEURAL NETWORK

This study presents a new procedure based on Artificial Neural Network (ANN) for identification of double cracks in Functionally Graded Beams (FGBs). A cantilever beam is modeled using Finite Element Method (FEM) for analyzing a double-cracked FGB and evaluation of its first four natural frequencies for different cracks depths and locations. The obtained FEM results are verified against available references. Furthermore, four Multi-Layer Perceptron (MLP) neural networks are employed for identification of locations and depths of both cracks of FGB. BackError Propagation (BEP) method is used to train the ANNs. The accuracy of predicted results shows that the proposed procedure is suitable for double cracks identification detection in FGBs. © 2013 IAU, Arak Branch. All rights reserved.

[1]  S. Loutridis,et al.  CRACK IDENTIFICATION IN BEAMS USING WAVELET ANALYSIS , 2003 .

[2]  Jie Yang,et al.  Free vibration and buckling analyses of functionally graded beams with edge cracks , 2008 .

[3]  Jinhee Lee.  IDENTIFICATION OF MULTIPLE CRACKS IN A BEAM USING NATURAL FREQUENCIES , 2009 .

[4]  Robert D. Adams,et al.  The location of defects in structures from measurements of natural frequencies , 1979 .

[5]  Murat Lüy,et al.  An analysis of cracked beam structure using impact echo method , 2005 .

[6]  Andrew D. Dimarogonas,et al.  Vibration of cracked structures: A state of the art review , 1996 .

[7]  F. Erdogan,et al.  The Surface Crack Problem for a Plate With Functionally Graded Properties , 1997 .

[8]  Fulei Chu,et al.  Identification of crack in functionally graded material beams using the p-version of finite element method , 2009 .

[9]  Keith Worden,et al.  Structural fault diagnosis and isolation using neural networks based on response-only data , 2003 .

[10]  Jian-Da Wu,et al.  Faulted gear identification of a rotating machinery based on wavelet transform and artificial neural network , 2009, Expert Syst. Appl..

[11]  Yang Xiang,et al.  Free and forced vibration of cracked inhomogeneous beams under an axial force and a moving load , 2008 .

[12]  James H. Garrett,et al.  Use of neural networks in detection of structural damage , 1992 .

[13]  S. K. Maiti,et al.  Detection of multiple cracks using frequency measurements , 2003 .

[14]  Baris Binici,et al.  Vibration of beams with multiple open cracks subjected to axial force , 2005 .

[15]  Jie Yang,et al.  Nonlinear vibration of edge cracked functionally graded Timoshenko beams , 2009 .

[16]  N. T. Khiem,et al.  A SIMPLIFIED METHOD FOR NATURAL FREQUENCY ANALYSIS OF A MULTIPLE CRACKED BEAM , 2001 .

[17]  S. Masoud,et al.  EFFECT OF CRACK DEPTH ON THE NATURAL FREQUENCY OF A PRESTRESSED FIXED–FIXED BEAM , 1998 .

[18]  T. Chondros,et al.  Identification of cracks in welded joints of complex structures , 1980 .

[19]  Mustafa Sabuncu,et al.  Vibration analysis of multiple-cracked non-uniform beams , 2009 .

[20]  A. S. Sekhar,et al.  Multiple cracks effects and identification , 2008 .

[21]  Z. C. He,et al.  Crack detection of arch dam using statistical neural network based on the reductions of natural frequencies , 2007 .

[22]  M. Şi̇mşek.  NON-LINEAR VIBRATION ANALYSIS OF A FUNCTIONALLY GRADED TIMOSHENKO BEAM UNDER ACTION OF A MOVING HARMONIC LOAD , 2010 .

[23]  T. Chondros,et al.  Analytical Methods in Rotor Dynamics , 1983 .

[24]  Shih-Lin Hung,et al.  Detection of structural damage via free vibration responses generated by approximating artificial neural networks , 2003 .

[25]  J. Rice,et al.  Elementary engineering fracture mechanics , 1974 .

[26]  J. E. Taylor,et al.  An identification problem for vibrating cracked beams , 1991 .