Paper
1 August 2003 Joint degradation assessment in an extended structure using chaotic attractor property analysis
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Abstract
Recently, a new approach in vibration-based structural health monitoring has been developed utilizing features extracted from concepts in nonlinear dynamics systems theory. The structure is excited with a low-dimensional chaotic input, and the steady-state structural response attractor is reconstructed using a false nearest neighbors algorithm. Certain features have been computed from the attractor such as average local "neighborhood" variance, and these features have been shown in previous works to exceed the damage resolving capability of traditional modal-based features in several computational and experimental studies. In this work, we adopt a similar attractor approach, but we present a feature based on nonlinear predictive models of evolving attractor geometry. This feature has an advantage over previous attractor-based features in that the input excitation need not be monitored. We apply this overall approach to a steel frame model of a multi-story building, where damage is incurred by the loosening of bolted connections between model members.
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Michael D. Todd, Jeannette R. Wait, Jonathan M. Nichols, and Stephen T. Trickey "Joint degradation assessment in an extended structure using chaotic attractor property analysis", Proc. SPIE 5047, Smart Nondestructive Evaluation and Health Monitoring of Structural and Biological Systems II, (1 August 2003); https://doi.org/10.1117/12.483978
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KEYWORDS
Sensors

Data modeling

Aluminum

Transducers

Feature extraction

Structural health monitoring

Analytical research

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