By Brian Walsh & Arturo González
description
Transcript of By Brian Walsh & Arturo González
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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 6th European Framework Project ARCHES for their generous support
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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
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1. Introduction to NNs
Synapses
Cell Body
Activation Function
Weighted Connections
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1. Introduction to NNs
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2. Damaged Beam Simulation
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2. Damaged Beam Simulation
Reduced Stiffness
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2. Damaged Beam Simulation
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3. Network Training
Error BP
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4. Results
Net Output Category
Net indicates lowest EI value in correct element
Net indicates lowest EI value in correct element, and healthy elements elsewhere
EIpredicted / EItarget < 1.03
Best performance Category
Location Identified
EI Profile Identified
Severity Estimated
Beam Identified
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4. Results
4.1 Number of Nodes in Hidden Layer
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4. Results
4.1 Number of Nodes in Hidden Layer
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4. Results
4.2 Number of Input Nodes
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4. Results
4.3 Size of Training Set
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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!