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Structural Health Monitoring Using an Integrated Digital Twin in the Time-Frequency Domain

Mollaei, Sobhan | 2025

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 58264 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Bakhshi, Ali
  7. Abstract:
  8. This study presents a novel framework for structural health monitoring (SHM) using a digital twin, capable of early damage detection, localization, and severity assessment. System identification is performed through online operational modal analysis, utilizing frequency response function (FRF) data across different time windows. The monitoring system employs two approaches: a data-driven approach for detecting the presence of damage and a model-based approach for determining its location and severity. In the data-driven approach, a Hankel matrix is constructed from FRF data, and the subspace angle is computed on principal components to identify damage. In the model-based approach, sensitivity analysis of the principal components of FRF data is used to pinpoint the location and quantify the severity of damage. Due to the unavailability of real data, simulated data were used and evaluated via the Monte Carlo method. The proposed algorithms effectively detect damage, locate it, and assess its severity even with up to 20% noise, suggesting potential effectiveness with real-world data. This framework enhances SHM processes and can reduce maintenance costs
  9. Keywords:
  10. Structural Health Monitoring ; Digital Twin ; Operational Modal Analysis ; Principal Component Analysis (PCA) ; Sensitivity Analysis ; Structural Damage Detection (SDD) ; Model-Based Damage Detection ; Data-Driven Damage Detection

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