Smart Structures and Systems

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Structural damage identification with output-only measurements using modified Jaya algorithm and Tikhonov regularization method

  • Guangcai Zhang (Key Laboratory of concrete and prestressed concrete structure of Ministry of Education, Southeast University) ;
  • Chunfeng Wan (Key Laboratory of concrete and prestressed concrete structure of Ministry of Education, Southeast University) ;
  • Liyu Xie (Research Institute of Structural Engineering and Disaster Reduction, College of Civil Engineering, Tongji University) ;
  • Songtao Xue (Research Institute of Structural Engineering and Disaster Reduction, College of Civil Engineering, Tongji University)
  • Received : 2022.10.20
  • Accepted : 2023.01.03
  • Published : 2023.03.25
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Abstract

The absence of excitation measurements may pose a big challenge in the application of structural damage identification owing to the fact that substantial effort is needed to reconstruct or identify unknown input force. To address this issue, in this paper, an iterative strategy, a synergy of Tikhonov regularization method for force identification and modified Jaya algorithm (M-Jaya) for stiffness parameter identification, is developed for damage identification with partial output-only responses. On the one hand, the probabilistic clustering learning technique and nonlinear updating equation are introduced to improve the performance of standard Jaya algorithm. On the other hand, to deal with the difficulty of selection the appropriate regularization parameters in traditional Tikhonov regularization, an improved L-curve method based on B-spline interpolation function is presented. The applicability and effectiveness of the iterative strategy for simultaneous identification of structural damages and unknown input excitation is validated by numerical simulation on a 21-bar truss structure subjected to ambient excitation under noise free and contaminated measurements cases, as well as a series of experimental tests on a five-floor steel frame structure excited by sinusoidal force. The results from these numerical and experimental studies demonstrate that the proposed identification strategy can accurately and effectively identify damage locations and extents without the requirement of force measurements. The proposed M-Jaya algorithm provides more satisfactory performance than genetic algorithm, Gaussian bare-bones artificial bee colony and Jaya algorithm.

Keywords

Acknowledgement

This work was supported by the Key Program of Intergovernmental International Scientific and Technological Innovation Cooperation (2021YFE0112200), the Japan Society for Promotion of Science (Kakenhi No. 18K04438), and the Tohoku Institute of Technology research Grant. These financial supports are sincerely appreciated. Besides, the author would like to thank the anonymous reviewers for their detailed and fruitful remarks.

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