Technical Papers
Aug 25, 2022

Multiorder Detection of Bridge Modal-Frequency Anomalies Considering Multiple Environmental Factors

Publication: Journal of Performance of Constructed Facilities
Volume 36, Issue 6

Abstract

Because bridge modal frequency is inevitably influenced by environmental factors, and single-order frequency is possibly insensitive to some damage conditions, frequency anomaly detection will fail. Therefore, conducting overall multiorder modal frequency anomaly detection is essential considering multiple environmental factors. This paper focuses on identifying multiorder modal frequency anomalies from the perspective of probability. The Gaussian process regression (GPR) model is first established to map the multiple environmental factors to the modal frequencies, whose prediction results consist of frequency estimations with uncertainties. Then, the single- and multiorder modal frequency anomaly characteristic indices are derived by conditional probability and Bayes’ theorem, respectively. Multiorder modal frequency anomaly detection is finally conducted after setting a threshold value. Two groups of GPR models with temperature and environmental inputs are verified in a cable-stayed bridge case. The proposed anomaly detection method can take into account the insensitivity of low-order frequencies to simulated frequency reduction conditions and accurately identify anomalous frequencies affected by multiple environmental factors.

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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 on reasonable request.

Acknowledgments

This research work was jointly supported by the National Natural Science Foundation of China (Grant Nos. 51978128 and 52078102), and the Fundamental Research Funds for the Central Universities (Grant No. DUT22ZD213).

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Go to Journal of Performance of Constructed Facilities
Journal of Performance of Constructed Facilities
Volume 36Issue 6December 2022

History

Received: Nov 11, 2021
Accepted: Jun 1, 2022
Published online: Aug 25, 2022
Published in print: Dec 1, 2022
Discussion open until: Jan 25, 2023

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Kai-Chen Ma, S.M.ASCE [email protected]
Ph.D. Candidate, School of Civil Engineering, Dalian Univ. of Technology, Dalian 116023, China. Email: [email protected]
Ting-Hua Yi, M.ASCE [email protected]
Professor, School of Civil Engineering, Dalian Univ. of Technology, Dalian 116023, China (corresponding author). Email: [email protected]
Dong-Hui Yang, M.ASCE [email protected]
Associate Professor, School of Civil Engineering, Dalian Univ. of Technology, Dalian 116023, China. Email: [email protected]
Hong-Nan Li, F.ASCE [email protected]
Professor, School of Civil Engineering, Dalian Univ. of Technology, Dalian 116023, China. Email: [email protected]
Hua Liu, Ph.D. [email protected]
Chief Engineer, China Railway Bridge and Tunnel Technologies Co., Ltd., Nanjing 210061, China. Email: [email protected]

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