Vibration-based structural health monitoring using output-only measurements under changing environment

• Published in: Mechanical systems and signal processing Vol. 22; no. 1; pp. 34 - 56
• Main Authors: Deraemaeker, A., Reynders, E., De Roeck, G., Kullaa, J.
• Format: Journal Article
• Language: English
• Published: London Elsevier Ltd 2008; Elsevier
• Subjects: Automatic stochastic subspace identification; Damage detection; Environmental effects; Exact sciences and technology; Factor analysis; Fracture mechanics (crack, fatigue, damage...); Fundamental areas of phenomenology (including applications); Measurement and testing methods; Modal filters; Output-only measurements; Physics; Solid mechanics; Spatial filtering; Statistical process control; Structural and continuum mechanics; Structural health monitoring; Vibration, mechanical wave, dynamic stability (aeroelasticity, vibration control...); Statistical process control; Output-only measurements; Factor analysis; Damage detection; Modal filters; Automatic stochastic subspace identification; Structural health monitoring; Spatial filtering; Environmental effects; Fourier transformation; Structure integrity; Vibration measurement; Modeling; Vibrometer; Failure analysis; Monitoring; Damaging; Control chart; Vibration; Probabilistic approach; Subspace method; Bridges; Mode filter; Medium effect; Signal processing; Environmental effect; Spatial filters; Defect detection
• ISSN: 0888-3270; 1096-1216
• DOI: 10.1016/j.ymssp.2007.07.004

This paper deals with the problem of damage detection using output-only vibration measurements under changing environmental conditions. Two types of features are extracted from the measurements: eigenproperties of the structure using an automated stochastic subspace identification procedure and peak indicators computed on the Fourier transform of modal filters. The effects of environment are treated using factor analysis and damage is detected using statistical process control with the multivariate Shewhart- T control charts. A numerical example of a bridge subject to environmental changes and damage is presented. The sensitivity of the damage detection procedure to noise on the measurements, environment and damage is studied. An estimation of the computational time needed to extract the different features is given, and a table is provided to summarize the advantages and drawbacks of each of the features studied.