东南大学学报（自然科学版）2026，Vol.56Issue(4)：523-529,7.DOI:10.3969/j.issn.1001-0505.2026.04.004
基于同步压缩小波变换与手机传感器的大跨桥梁自振频率识别
Natural frequency identification of long-span bridges using synchrosqueezed wavelet transform and smartphone sensors
摘要
Abstract
This study investigates the potential of smartphones as sensors for bridge structural health monitor-ing(SHM)and proposes a natural frequency identification method based on synchrosqueezed wavelet trans-form(SWT)and spatiotemporal aggregation extreme value extraction.The method first extracts the time-fre-quency features of vibration signals using SWT and then aggregates the most bridge-relevant components in the spatial domain to analyze the natural frequencies of the bridge.Field driving tests were conducted on Shanghai Yangpu Bridge and Lupu Bridge,where acceleration and Global Navigation Satellite System(GNSS)data were collected using built-in smartphone sensors.A sensitivity analysis was performed to evaluate the influ-ence of sample size,frequency bandwidth,and Gaussian kernel width on the identification accuracy.The re-sults demonstrate that the proposed method can accurately identify the first three vertical modal frequencies of the bridge.Although the accuracy does not match that of traditional SHM-based modal identification,the ap-proach provides a cost-effective and efficient solution for structural condition assessment,particularly suitable for large-scale bridges where conventional SHM systems are economically unfeasible.关键词
同步压缩小波变换/结构健康监测/移动监测/加速度响应Key words
synchrosqueezed wavelet transform/structural health monitoring/mobile sensing/acceleration responses分类
交通工程引用本文复制引用
宋明明,贾靖垚,夏烨,龚丰宗,凌子睿,孙利民..基于同步压缩小波变换与手机传感器的大跨桥梁自振频率识别[J].东南大学学报（自然科学版）,2026,56(4):523-529,7.基金项目
国家自然科学基金青年基金资助项目(52208199) （52208199）
上海勘测设计研究院有限公司上海海上风能资源开发利用工程技术研究中心开放课题资助项目(FNZX2023KP01). （FNZX2023KP01）
