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Structural Health Monitoring Using Optimal Finite Element Model Based on Digital Image Correlation

Amir Hossein Amir Ahmadi | 2023

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 56286 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Khaloo, Alireza
  7. Abstract:
  8. The purpose of this research is to monitor the health of structures using the updated finite element model, in which digital images are used to optimize the numerical model. Structural Health Monitoring (SHM) is always an important and significant issue that has attracted the attention of many researchers in recent years. In general, some researches have been conducted in this field using physical sensors that provide discrete data to the system for analysis. Using cameras to monitor the structure makes it possible to extract continuous and integrated data from the structure using digital images, which is a significant advantage compared to physical sensors.In this research, a steel cantilever beam is subjected to a concentrated load at its free end. During loading, the beam is recorded by digital cameras, and by using the Digital Image Correlation (DIC) method, the amount of displacement and strain is obtained. Also, DIC measurements are validated by installing an LVDT sensor and two strain gauges. In the following, using optimization algorithms, the finite element model of the structure is updated and the unknown parameters are determined. In the optimization process, a hybrid algorithm has been proposed, which is used to update the finite element model. This algorithm is a combination of particle swarm algorithm and Powell algorithm. With the help of the proposed algorithm, the unknown parameters have been determined with high accuracy and the errors have been minimized. Finally, by using the optimized model of the structure, the performance of the structure can be examined well
  9. Keywords:
  10. Optimization ; Digital Image Correlation ; Structural Health Monitoring ; Particles Swarm Optimization (PSO) ; Finite Element Model Updating ; Powell Optimization Algorithm

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