Multiorder Frequency-Based Integral Performance Warning of Bridges Considering Multiple Environmental Effects
Publication: Practice Periodical on Structural Design and Construction
Volume 28, Issue 2
Abstract
Modal frequency is widely utilized to reveal the health status of bridges; however, its warning capability may be reduced due to changing environmental conditions, i.e., the variations in temperature, humidity, and wind speed. Besides, accurately tackling these problems related to the high-dimensionality of environmental data, multivariate prediction of multiorder frequencies, reasonable quantification of the environment-caused modal variability, and the nonnormal distribution limitation of data are also a prerequisite for high-quality integral performance warning of bridges. Consequently, a multiorder frequency-based performance warning method for bridges is presented in this paper. Multivariate partial least squares analysis is first employed to extract the predominant feature vectors of environmental factors, which are sensitive to measured multiorder frequencies, for dimensionality reduction. After that, the environment-induced modal variability can be quantified with the derived frequency correction formula. Based on this, a performance warning index is constructed based on the support vector data description, which aims to address the problem associated with the nonnormal distribution of model errors and further strengthen the warning capability of frequency abnormality. The test results on a cable-stayed bridge indicate that the variation of normalized frequency tends to be more relatively stable, and the slight abnormal mutations of multiorder frequencies are timely detected, whose warning rates increase as the performance degradation, significance levels and considered modal orders increase.
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Data Availability Statement
All data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This research work was jointly supported by the National Natural Science Foundation of China (Grant Nos. 52250011, 51978128, and 52078102) and the Fundamental Research Funds for the Central Universities (Grant Nos. DUT22ZD213 and DUT22QN235).
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© 2023 American Society of Civil Engineers.
History
Received: Mar 6, 2022
Accepted: Dec 18, 2022
Published online: Feb 14, 2023
Published in print: May 1, 2023
Discussion open until: Jul 14, 2023
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