A neural network approach for structural identification and diagnosis of a building from seismic response data. - Huang, C.S (Earthquake engineering & structural dynamics.)
This work presents a novel procedure for identifying the dynamic characteristics of a building and diagnosing whether the building has been damaged by earthquakes, using a back propagation neural network approach. The dynamic characteristics are directly evaluated from the weighting matrices of the neural network trained by observed acceleration responses and input base excitations. Whether the building is damaged under a large earthquake is assessed by comparing the modal parameters and responses for this large earthquake with those for a small earthquake that has not caused this building any damage. The feasibility of the approach is demonstrated through processing the dynamic responses of a five storey steel frame, subjected to different strengths of the Kobe earthquake, in shaking table tests.