Local damage assessment of a building using Support Vector Machine

H. Hagiwara, A. Mita

研究成果: Article査読


A damage detection method utilizing the Support Vector Machine (SVM) is proposed. The SVM is a powerful pattern recognition tool applicable to complicated classification problems. Modal frequencies of a structure are used for pattern recognition in the proposed method. Typically, only two vibration sensors detecting a single input and a single output for a structural system can easily determine modal frequencies. For training SVMs the relationship between changes normalised by original modal frequencies, before suffering any damage, is utilized. The SVM trained for single damage was also found to be effective for detecting damage in multiple stories. The SVM based damage assessment is able to identify damage qualitatively as well as quantitatively.

ジャーナルWIT Transactions on the Built Environment
出版ステータスPublished - 2003 1 1

ASJC Scopus subject areas

  • 建築
  • 土木構造工学
  • 建築および建設
  • 自動車工学
  • 安全性、リスク、信頼性、品質管理
  • 人文科学(その他)
  • 輸送
  • 安全研究
  • コンピュータ サイエンスの応用


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