Beam definitions are used to simplify complex structures like bridges or skyscrapers. This study highlights the importance of monitoring beams as they are often the critical components and damage in them can result in changes in their dynamic characteristics. This study proposes a substructure-based approach for damage estimation in structural beams, that can later be extended for monitoring high-dimensional structures. The traditional approach of full structure monitoring mandates heavy instrumentation and computational costs. To avoid that, the existing subdomain estimation approaches need to deal with the quasi-static displacement at subdomain boundaries making the estimation a coupled problem. Instead, the proposed approach focuses on only monitoring a subdomain of interest, independently, making it computationally cheaper. The study employs an interacting filtering algorithm with Particle and Ensemble Kalman filters, circumventing the complexities of quasi-static displacement. The proposed approach has been tested numerically and the results are promising for further investigation and improvement.

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Identifying the Cracks in Beam Structures Using a Simplified Substructure Technique

  • Eshwar Kuncham,
  • Md Armanul Hoda,
  • Subhamoy Sen

摘要

Beam definitions are used to simplify complex structures like bridges or skyscrapers. This study highlights the importance of monitoring beams as they are often the critical components and damage in them can result in changes in their dynamic characteristics. This study proposes a substructure-based approach for damage estimation in structural beams, that can later be extended for monitoring high-dimensional structures. The traditional approach of full structure monitoring mandates heavy instrumentation and computational costs. To avoid that, the existing subdomain estimation approaches need to deal with the quasi-static displacement at subdomain boundaries making the estimation a coupled problem. Instead, the proposed approach focuses on only monitoring a subdomain of interest, independently, making it computationally cheaper. The study employs an interacting filtering algorithm with Particle and Ensemble Kalman filters, circumventing the complexities of quasi-static displacement. The proposed approach has been tested numerically and the results are promising for further investigation and improvement.