Baseline-free real-time assessment of structural changes

• Published in: Structure and infrastructure engineering Vol. 11; no. 2; pp. 145 - 161
• Main Authors: Santos, João P., Orcesi, André D., Crémona, Christian, Silveira, Paulo
• Format: Journal Article
• Language: English
• Published: Taylor & Francis 01.02.2015
• Subjects: Algorithms; Assessments; Bridges (structures); cluster analysis; Maintenance; Real time; real-time assessment; Rehabilitation; Strategy; Structural health monitoring; suspended bridges; symbolic data
• ISSN: 1573-2479; 1744-8980
• DOI: 10.1080/15732479.2013.858169

This article addresses the subject of data-driven structural health monitoring and proposes a real-time strategy to conduct structural assessment without the need to define a baseline period, in which the monitored structure is assumed healthy and unchanged. Independence from baseline references is achieved using unsupervised discrimination machine-learning methods, widely known as clustering algorithms, which are able to find groups in data relying only on their intrinsic features and without requiring prior knowledge as input. Real-time capability is based on the definition of symbolic data, which allows describing large amounts of information without loss of generality or structural-related information. The efficiency of the proposed methodology is illustrated using an experimental case study in which structural changes were imposed to a suspended bridge during an extensive rehabilitation programme. A single-value novelty index capable of describing multi-sensor data is proposed, and its effectiveness in identifying structural changes in real time, using outlier analysis, is discussed.