Abstract
Power transmission towers (PTTs) are critical components of electrical grids; however, their slender nature makes them vulnerable to collapse due to environmental degradation, inadequate maintenance, and extreme weather conditions. To mitigate these risks, reliable and cost-effective structural health monitoring (SHM) methods are required to detect early signs of structural deterioration.This study proposes a vibration-based approach using spectral-domain damage indicators to assess structural integrity. By analyzing changes in frequency response functions (FRFs), the method eliminates the need for traditional modal identification, simplifying indicator construction and reducing computational complexity. Validation is conducted through numerical simulations using a finite element (FE) model and experimental tests on a downscaled PTT model via experimental modal analysis (EMA). As a first approach, this study specifically focuses on the structural health assessment of an isolated, free-standing structure, excluding the complex dynamic interactions inherent to power transmission line systems.Results demonstrate that the proposed indicator accurately tracks structural modifications and provides clear, interpretable insights with significantly lower computational cost than existing spectral-domain SHM techniques. Furthermore, it requires only a minimal sensor setup, making it well-suited for practical field applications. While validated using EMA, the method is designed for straightforward extension to operational modal analysis (OMA), offering a practical alternative that enhances the early detection of structural degradation and supports preventive maintenance strategies.
| Original language | English |
|---|---|
| Article number | 122810 |
| Number of pages | 20 |
| Journal | Engineering Structures |
| Volume | 361 |
| DOIs | |
| Publication status | Published - 15 Aug 2026 |
Keywords
- Cross-correlation
- Frequency response functions
- Power transmission towers
- Structural health monitoring
- Vibration-based assessment
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