Operational influence line identification of bridge cable forces using stochastic vehicle-induced responses

The cable force influence line (CFIL) is an important tool for studying the structural behavior and performance status of stay cables under moving vehicles, such as damage identification, fatigue evaluation, extreme load effect analysis, etc. The traditional method of influence line identification relies mainly on the field testing, which involves high costs, complicated procedures and traffic interruption during testing. Therefore, this paper proposes a novel method for identifying CFIL under stochastic traffic flow during operation. Based on the symmetrical characteristics of the cables on both sides, the concept of the vehicle-induced cable force sum (CFS) is first defined in this study. By integrating the CFS response to obtain the time-history area, the relationship between the influence line area (ILA) and stochastic vehicle loads is established. The inversion of CFS influence lines is then realized using the automatic recognition and processing algorithm of single-vehicle pulse segments. To further obtain the CFIL on one side, the cable force ratio index is introduced to decouple and allocate the obtained CFS influence line. Finally, a numerical example of a long-span cable-stayed bridge is provided to verify the feasibility of the proposed method. The results demonstrate that this study presents a practical and effective method for CFIL identification of bridge cables with satisfactory identification accuracy and low cost.