1996 # An Application of Genetic Algorithms to Identify Damage in Elastic Structures

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(89 citation statements)

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“…The predicted stiffness factors by the CCGA are almost the same as the actual stiffness factors for the cases without noise in the vibration characteristics as shown in Tables 4-7. Although there is the noise in natural frequencies and mode shapes, Tables 8-11 Predicted Figures 8,9,10,11,12,13,14, and 15 plot the predicted stiffness factors obtained from the CCGA versus the number of generated solutions for cases (a)-(d) without noise and with noise in the vibration characteristics, respectively. Similar to the first test problem, the stiffness factors searched by the CCGA are quickly converged to the good solutions including the cases that consider the noise in the vibration characteristics.…”

confidence: 99%

“…The predicted stiffness factors by the CCGA are almost the same as the actual stiffness factors for the cases without noise in the vibration characteristics as shown in Tables 4-7. Although there is the noise in natural frequencies and mode shapes, Tables 8-11 Predicted Figures 8,9,10,11,12,13,14, and 15 plot the predicted stiffness factors obtained from the CCGA versus the number of generated solutions for cases (a)-(d) without noise and with noise in the vibration characteristics, respectively. Similar to the first test problem, the stiffness factors searched by the CCGA are quickly converged to the good solutions including the cases that consider the noise in the vibration characteristics.…”

confidence: 99%

“…A number of works employed GAs to solve the structural damage detection problems such as [5,6,[11][12][13][14][15][16]. Rao et al [5] used a two-point crossover binary coded GA with tournament selection for reproduction of population.…”

confidence: 99%

“…On the other hand, Araújo et al (2006); Araújo et al (2002) proposed an inverse problem to obtain the constitutive properties of composite plate specimens with surface bonded piezoelectric patches or layers, where the cost functional was the difference between the experimental and FEM-predicted eigen-frequencies and its minimization was carried out using two strategies: a gradient-based method, and neural networks. A genetic algorithm was applied by Chou & Ghaboussi (2001) and Mares & Surace (1996) to solve the IP in elastic structures. Based on crystallographic criteria by Russell & Ghomshei (1997) a cost functional was formulated as the difference in the orientation distribution function, which provides a statistical description of the orientation.…”

confidence: 99%

“…Cunha et al (1999) use genetic algorithm to estimate the stiffness coefficients by minimizing a residual formed from the Eigen solutions. Another example of the use of genetic algorithm for the determination of stiffness reduction is Mares and Surace (1996). The main drawback of the above methodologies is that causes of structural behavior cannot be easily determined using the values of stiffness coefficients.…”

confidence: 99%