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Neural Network Damage Detection for Bridges by Guilherme Porto is a document available to read on EtoBox.
What is Neural Network Damage Detection for Bridges about?
The document presents a neural networks-based technique for detecting damage in bridges using modal data, focusing on input parameters that are less sensitive to modeling errors. A case study involving a steel girders and RC slabs bridge demonstrated successful detection of various damage cases and accurate identification of damage locations, though some minor false alarms were noted in damage severity estimates. The approach utilizes pattern recognition through an artificial neural network (ANN) with speci
- Author
- Guilherme Porto
- Language
- EN