Abstract
Bat algorithm (BA) has been widely used to solve optimization problems in different fields. However, there are still some shortcomings of standard BA, such as premature convergence and lack of diversity. To solve this problem, a modified directional bat algorithm (MDBA) is proposed in this paper. Based on the directional bat algorithm (DBA), the individual optimal updating mechanism is employed to update a bat’s position by using its own optimal solution. Then, an elimination strategy is introduced to increase the diversity of the population, in which individuals with poor fitness values are eliminated, and new individuals are randomly generated. The proposed algorithm is applied to the structural damage identification and to an objective function composed of the actual modal information and the calculated modal information. Finally, the proposed MDBA is used to solve the damage detection of a beam-type bridge and a truss-type bridge, and the results are compared with those of other swarm intelligence algorithms and other variants of BA. The results show that in the case of the same small population number and few iterations, MDBA has more accurate identification and better convergence than other algorithms. Moreover, the study on anti-noise performance of the MDBA shows that the maximum relative error is only 5.64% at 5% noise level in the beam-type bridge, and 6.53% at 3% noise in the truss-type bridge, which shows good robustness.
Highlights
Due to the diversity of loads and the complexity of working environment, civil engineering structures often suffer various damages during service, such as concrete cracking, steel yield and so on
Most of the above-mentioned swarm intelligence optimization algorithm (SIOA) have achieved good success in solving constrained optimization problems of structural damage identification, there are still problems like large population and too many iterations, which lead to complex calculation and long calculation time, especially when using structural response data as the error objective function
Under the condition of a small population and few iterations, all four algorithms could accurately find the location of structural damage, but the modified directional bat algorithm (MDBA) had the best identification accuracy in damage degree and the best and fastest convergence
Summary
Due to the diversity of loads and the complexity of working environment, civil engineering structures often suffer various damages during service, such as concrete cracking, steel yield and so on. Most of the above-mentioned SIOAs have achieved good success in solving constrained optimization problems of structural damage identification, there are still problems like large population and too many iterations, which lead to complex calculation and long calculation time, especially when using structural response data as the error objective function. In order to distinguish the sensitivity of natural frequency, mode shape and flexibility matrix in structural damage identification, the objective function is weighted [21,43]. When different swarm intelligence algorithms [42,43,45] were employed to identify the same structure of 10-element beam, a large number of populations and iterations were required. Und10eorf t1h5e condition of a small population and few iterations, MDBA showed good identification results and robustness in the case of different noises
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