Detecting Cable Force Anomalies on Cable-Stayed Bridges Using the STA/LTA Method

Yanwei Wang, Qingxu Zhao, Yuandi Li, Min Zhang and Wanxu Zhu ()
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Yanwei Wang: Guangxi Key Laboratory of Geomechanics and Geotechnical Engineering, Guilin University of Technology, Guilin 541004, China
Qingxu Zhao: Guangxi Key Laboratory of Geomechanics and Geotechnical Engineering, Guilin University of Technology, Guilin 541004, China
Yuandi Li: Guangxi Key Laboratory of Geomechanics and Geotechnical Engineering, Guilin University of Technology, Guilin 541004, China
Min Zhang: Guangxi Key Laboratory of Geomechanics and Geotechnical Engineering, Guilin University of Technology, Guilin 541004, China
Wanxu Zhu: Guangxi Key Laboratory of Geomechanics and Geotechnical Engineering, Guilin University of Technology, Guilin 541004, China

Sustainability, 2022, vol. 14, issue 18, 1-12

Abstract: The cable force of cable-stayed bridges may become abnormal during operation, so cable force anomaly detection is essential for evaluating the health of cables. The current methods for detecting cable force anomalies have poor resistance to temperature disturbances and are insensitive to abnormal cable force, making it challenging to detect minor cable force anomalies. Therefore, this work employs the short-time-average over long-time-average (STA/LTA) method to detect cable force anomalies. The characteristic function and key parameters of the STA/LTA method are optimized and tested by combining measured cable force data with cable force anomaly simulation. The results show that the STA/LTA method can effectively mitigate the interference of temperature in the detection of cable force anomalies and that it has good sensitivity to minor cable force anomalies. By examining detecting the measured cable force data of the Xiangjiang Bridge in Dongzhou, Hengyang, China, it is further verified that the STA/LTA method could effectively detect a cable force anomaly with a cable force deviation rate of higher than 1%.

Keywords: cable-stayed bridge; cable force; anomaly detection; STA/LTA (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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