Structural health monitoring of bridges: a model-free ANN-based approach to damage detection
Author:
Publisher
Springer Science and Business Media LLC
Subject
Safety, Risk, Reliability and Quality,Civil and Structural Engineering
Link
http://link.springer.com/article/10.1007/s13349-017-0252-5/fulltext.html
Reference29 articles.
1. Huang Y, Ludwig SA, Deng F (2016) Sensor optimization using a genetic algorithm for structural health monitoring in harsh environments. J Civ Struct Health Monit 6(3):509–519
2. Li J, Zhang X, Xing J, Wang P, Yang Q, He C (2015) Optimal sensor placement for long-span cable-stayed bridge using a novel particle swarm optimization algorithm. J Civ Struct Health Monit 5(5):677–685
3. Yi T-H, Li H-N, Wang C-W (2016) Multiaxial sensor placement optimization in structural health monitoring using distributed wolf algorithm. Struct Control Health Monit 23(4):719–734
4. Jin C, Jang S, Sun X, Li J, Christenson R (2016) Damage detection of a highway bridge under severe temperature changes using extended Kalman filter trained neural network. J Civ Struct Health Monit 6(3):545–560
5. Farrar CR, Worden K (2013) Structural health monitoring. A machine learning perspective. Wiley, Hoboken
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