Research on Damage Identification in Transmission Tower Structures Based on Cross-Correlation Function Amplitude...

Area of Science:

• Structural Engineering
• Civil Engineering
• Infrastructure Monitoring

Background:

• Transmission towers are critical power infrastructure requiring robust structural health monitoring.
• Long-term service can lead to cumulative structural damage, necessitating effective identification methods.
• Existing methods may require complex analysis or extensive sensor networks.

Purpose of the Study:

• To present a novel cross-correlation function amplitude vector (CorV) method for damage localization in transmission towers.
• To validate the method's efficacy through numerical simulations and experimental testing.
• To establish a practical approach for structural health monitoring under environmental excitation.

Main Methods:

• Development of the CorV method based on time-domain response analysis.
• Quantification of damage using the CorV assurance criterion (CVAC).
• Damage localization through first-order differencing of CorV components and analysis of dynamic response signals.

Main Results:

• The CVAC value significantly decreases in damaged structures compared to healthy states.
• Accurate damage localization is achieved by analyzing relative changes in CorV components.
• The method successfully detected both the existence and location of simulated damage in a transmission tower model.

Conclusions:

• The CorV method provides an effective and accurate means for damage localization in transmission towers.
• The approach requires only time-domain response signals under random excitation, simplifying data acquisition.
• This technique is highly suitable for continuous structural health monitoring of transmission towers subjected to environmental factors.