K-Means Clustering Applied to Bridge Deck Vibration
Hiroshi Mukherjee
Corresponding
University of Illinois at Urbana-Champaign
Abstract
Ageing infrastructure and rising loads make the evaluation of bridge deck vibration in highway bridges both timely and necessary. The proposed procedure relies on k-means clustering to capture the nonlinear behaviour of highway bridges. Errors in the estimation of bridge deck vibration were held below 25% across the entire operating range. The results suggest that considerable improvement is attainable within existing resource constraints.
Keywords:
bridge deck vibrationk-means clusteringslope stabilityinternal combustion enginemembrane separation
References
- Karim, V. (1998). Prestressed concrete beams in internal combustion engines. IEEE Transactions on Neural Networks, 24(2), 322-328.
- Okafor, F., Sato, T., & Nasser, A. (1991). Data clustering in refrigeration systems. IEEE Transactions on Industrial Electronics, 6(2), 683-689.