State-monitoring for abnormal vibration of bridge cables focusing on non-stationary responses: From knowledge in phenomena to digital indicators

Abstract

Input-output characteristics in an event of the abnormal vibration of a kilometer-level railway-highway-combined cable-stayed bridge's cables under in-service winds are deeply investigated. The knowledge of commonality that cables' abnormal vibration exists multiple independent non-stationary sections in time series with high-amplitude and quasi-single-frequency is summarized. An automatic extraction of non-stationary section of abnormal vibration is conducted via Gaussian mixture modeling of the envelope of time series signal. A new process of modal parameter identification is presented using the data of non-stationary section after bandpass filtering and its last descent. It is demonstrated that the identified damping ratio of cables with abnormal vibration will be below 0.05%. Each abnormal non-stationary vibration's frequency, damping ratio, and wind speed are clustered into corresponding natural vibration modes. Correlation model of wind speed-vibration frequency is fitted by data centroid of clusters to predict the possible-occurrence frequency of an abnormal non-stationary vibration before it is fully completed.