Quasi-Static Influence Line Identification and Damage Identification of Equal-Span Bridges Based on Measured Vehicle-Induced Deflection

Abstract

The bridge influence line (IL) reflects the response of a certain section due to varying load positions. As a result, IL has a wide application prospect in damage identification and condition assessment. Up to date, studies regarding IL have been focused on the structure condition evaluation. A feasible and practical method for damage identification is still not yet available. The present paper proposes a comprehensive damage identification methodology based on IL under a moving vehicle is composed of data pre-processing, IL extraction, and damage detection. Firstly, a thorough review of existing IL identification methods based on signal processing is provided. Then three quasi-static IL identification methods based on measured data are discussed. Consequently, the study proposes a two-stage damage identification approach for simply supported bridges with equal span length. Also, the effectiveness of this approach is verified through field tests on a real girder bridge. At last, conclusions are drawn, and potential issues for the application of the proposed method in practice are discussed.