Effects of environmental and operational variability on structural health monitoring

• Published in: Philosophical transactions of the Royal Society of London. Series A: Mathematical, physical, and engineering sciences Vol. 365; no. 1851; pp. 539 - 560
• Main Author: Sohn, Hoon
• Format: Journal Article
• Language: English
• Published: London The Royal Society 15.02.2007
• Subjects: Algorithms; Bridge engineering; Bridges; Computer Simulation; Construction Materials - analysis; Damage Detection; Data Normalization; Datasets; Engineering - instrumentation; Engineering - methods; Environment; Environmental And Operational Variation; Environmental disorders; Environmental Monitoring - instrumentation; Environmental Monitoring - methods; Equipment Design; Equipment Failure Analysis - instrumentation; Equipment Failure Analysis - methods; Facility Design and Construction - instrumentation; Facility Design and Construction - methods; Maintenance - methods; Materials Testing - methods; Mathematical vectors; Models, Theoretical; Novelty detection; Principal components analysis; Signal Processing, Computer-Assisted; Structural health monitoring; Transducers; Vibration
• ISSN: 1364-503X; 1471-2962
• DOI: 10.1098/rsta.2006.1935

Stated in its most basic form, the objective of structural health monitoring is to ascertain if damage is present or not based on measured dynamic or static characteristics of a system to be monitored. In reality, structures are subject to changing environmental and operational conditions that affect measured signals, and these ambient variations of the system can often mask subtle changes in the system's vibration signal caused by damage. Data normalization is a procedure to normalize datasets, so that signal changes caused by operational and environmental variations of the system can be separated from structural changes of interest, such as structural deterioration or degradation. This paper first reviews the effects of environmental and operational variations on real structures as reported in the literature. Then, this paper presents research progresses that have been made in the area of data normalization.