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OA

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.