Railway bridge damage detection based on extraction of instantaneous frequency by Wavelet Synchrosqueezed Transform

Abstract In bridge structural health monitoring, typically the dynamic response of system is used to assess condition bridge. However, interaction between a and passing vehicle imposes non-stationarity on response, whereby modal parameters become time-dependent detecting damage, for example, based parameters, becomes challenging. Dynamic vehicle-bridge (VBI) responses have mainly been investigated damage detection through identifying signal singularities abrupt changes. The are usually associated with high-frequency components (relative natural frequencies), it demanding isolate damage-induced from those caused by either an operational condition, i.e., track irregularities, or noise. Unlike range, influence resonance frequency coupled has not fully explored. present study proposes shape instantaneous as sensitive feature in which dynamics can be excluded. This demonstrates feasibility approach applying Wavelet Synchrosqueezed Transform (WSST). this variation induced distinguished vehicle. Several scenarios that implemented numerically analyzed verify method’s performance. results demonstrate high resolution extracted VBI outperforms determining local disruption, leading damage. A Damage Index (DI) also proposed attempt quantify severity.