Automatic Modal Frequency Identification of Bridge Cables under Influence of Abnormal Monitoring Data
Publication: Journal of Performance of Constructed Facilities
Volume 38, Issue 6
Abstract
Automatic identification of modal frequencies can be used to directly estimate the real-time tension force of bridge cables and provide early damage alarming. However, a large amount of abnormal monitoring data usually exists in structural health monitoring (SHM) systems. Abnormal monitoring data may lead to faulty results of modal frequency identification and incorrect cable tension force estimation. Then, false or missing alarming of cable damage may arise. An automatic identification method of bridge cable modal frequencies under the influence of abnormal monitoring data is proposed in this study. The peak picking (PP) method is used to automatically obtain the original identification results of cable modal frequencies. To remove faulty frequency identification results, a multidimensional density-based clustering model is established. The cable acceleration data of the Waitan cable-stayed bridge are used to verify the accuracy of the proposed method. The influence of various abnormal monitoring data on frequency identification is investigated, and the accuracy of multidimensional clustering models is verified. The results show that abnormal monitoring data have a harmful influence on automatic modal frequency identification for bridge cables. The accuracy of the multidimensional clustering model for faulty frequency identification results is more than 99%. After removing the faulty frequency identification results, the correlation between the cable modal frequencies and environmental temperature becomes clearer and more reasonable.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This work was supported by the National Natural Science Foundation of China (51878027), Outstanding Youth Fund of Beijing University of Civil Engineering and Architecture (JDJQ20220802), and Fundamental Research Funds for Beijing University of Civil Engineering and Architecture (X20174).
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Information & Authors
Information
Published In
Journal of Performance of Constructed Facilities
Volume 38 • Issue 6 • December 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Oct 2, 2023
Accepted: Jun 14, 2024
Published online: Sep 13, 2024
Published in print: Dec 1, 2024
Discussion open until: Feb 13, 2025
ASCE Technical Topics:
- Automatic identification systems
- Bridge engineering
- Bridges
- Bridges (by type)
- Cable stayed bridges
- Cables
- Continuum mechanics
- Detection methods
- Dynamics (solid mechanics)
- Engineering fundamentals
- Engineering mechanics
- Equipment and machinery
- Methodology (by type)
- Model accuracy
- Models (by type)
- Motion (dynamics)
- Natural frequency
- Oscillations
- Solid mechanics
- Structural engineering
- Structural health monitoring
- Structural members
- Structural systems
- Tension members
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