journal article·2026-06-11

Baseline-free damage identification of a bridge based on the modal ingredients of the response principal components with limited sensors

Enguo Guo, Yuming Lin, Zimo Zhu, Hongwei Ma, Jun Li, Zhenhua Nie

Publisher page

Abstract

Bridges are exposed to structural damage under moving vehicle loads, posing potential threats to structural safety. To address the limitations of conventional mode-shape-based damage identification methods, which rely on baseline data and a large number of sensors, this article presents a novel approach based on response principal components under moving loads. Considering vehicle–bridge interaction, this study elucidates the composition of the response's principal components of damaged beams. Initially, the dynamic response of the beam is decomposed using the proper orthogonal decomposition, and the analytical expressions for the principal components of responses are derived. Then, damage identification is conducted, indicating that the principal components of the response for a damaged beam can be decomposed into modal components, dynamic components, and damage components. Moving average filtering is employed in the separation process, thereby extracting the damage component. Numerical simulations and experimental validations are subsequently conducted to assess algorithm performance. This study highlights the role of the damage component within principal components, providing new insights into their physical interpretation in structural damage identification.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Structural Health Monitoring Techniques · Ultrasonics and Acoustic Wave Propagation · Machine Fault Diagnosis Techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Jinan University

Key Laboratory of Marine Civil Engineering Materials and Structures, Ministry of Education of China, Guangzhou, Guangdong, China

Department of Education of Guangdong Province, The Key Laboratory of Green Toughening and Safety Prevention and Control of Offshore Structures, Guangdong, China

School of Environment and Civil Engineering, Dongguan University of Technology

Curtin University

Funding

National Natural Science Foundation of China · Fundamental Research Funds for the Central Universities

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