1. An Overview of the Application of Neural Networks to the Monitoring of Civil Engineering Structures By Brian Walsh & Arturo González With thanks thanks to the 6 th European Framework Project ARCHES for their generous support

2. Contents 1.Introduction to neural networks (NNs) 2.Damaged beam simulation 3.Network training 4.Results Number of hidden nodes Number of input nodes Size of training set

3. 1. Introduction to NNs Synapses Cell Body Activation Function Weighted Connections

4. 1. Introduction to NNs

5. 2. Damaged Beam Simulation

6. Reduced Stiffness

7. 2. Damaged Beam Simulation

8. 3. Network Training Error BP

9. 4. Results Net OutputCategory Net indicates lowest EI value in correct element Net indicates lowest EI value in correct element, and healthy elements elsewhere EI predicted / EI target < 1.03 Best performance Category Location Identified EI Profile Identified Severity Estimated Beam Identified

10. 4. Results 4.1 Number of Nodes in Hidden Layer

11. 4. Results 4.1 Number of Nodes in Hidden Layer

12. 4. Results 4.2 Number of Input Nodes

13. 4. Results 4.3 Size of Training Set

14. 5. Conclusions NNs can be an effective tool for damage detection NNs sensitive to number of nodes & training patterns Further work Thank you for listening!