A neural network approach for structural identification and diagnosis of a building from seismic response data

Chiung-Shiann Huang*, Shih-Lin Hung, C. M. Wen, T. T. Tu

*此作品的通信作者

研究成果: Article同行評審

97 引文 斯高帕斯(Scopus)

摘要

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.

原文English
頁(從 - 到)187-206
頁數20
期刊Earthquake Engineering and Structural Dynamics
32
發行號2
DOIs
出版狀態Published - 2月 2003

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