Damage indicator for building structures using artificial neural networks as emulators

Akira Mita, Yuyin Qian

研究成果: Conference contribution

抄録

Damage indicator for building structures using artificial neural networks (ANN) requiring only acceleration response is proposed. The ANN emulator used for emulating the structural response is tuned to properly model the hysteretic nature of building response. To facilitate the most realistic monitoring system using accelerometers, the acceleration streams at the same location but at different time steps were utilized. The prediction accuracy could be raised by the increment of number of acceleration streams at different time steps. In our proposed approach, damage occurrence alarm could be obtained practically and economically only using readily available acceleration time histories. Based on the numerical simulation for a 5-story shear structure, the adaptability, generality and appropriate parameter of the neural network were studied in. The damage is quantified by using relative root mean square (RRMS) error. Variant ground motions were used to certify the generality of this approach. The appropriate parameter of the neural network was suggested according to variant values of damage index corresponding to the different parameters.

本文言語English
ホスト出版物のタイトルSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2007
DOI
出版ステータスPublished - 2007
イベントSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2007 - San Diego, CA, United States
継続期間: 2007 3 192007 3 22

出版物シリーズ

名前Proceedings of SPIE - The International Society for Optical Engineering
6529 PART 2
ISSN(印刷版)0277-786X

Other

OtherSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2007
国/地域United States
CitySan Diego, CA
Period07/3/1907/3/22

ASJC Scopus subject areas

  • 電子材料、光学材料、および磁性材料
  • 凝縮系物理学
  • コンピュータ サイエンスの応用
  • 応用数学
  • 電子工学および電気工学

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