構造ヘルスモニタリング・損傷評価

[2033] 全層にセンサーを設置しない場合の建物の変形モードを分類するための特徴識別に関する研究

ヤオトレボー¹, 楠浩一¹ (1.東京大学)

キーワード：変形モード、構造ヘルスモニタリング、地震、安全限界、機械学習、Deformation mode、structural health monitoring、earthquake、safety limit、machine-learning

Building deformation mode identification, which is important for evaluating safety in structural health monitoring applications following seismic events, may be difficult to perform if there are some floors without sensors. This study proposed potential features based on the response of monitored floors which may indicate the correct deformation mode. These features were evaluated against shake-table test data of steel frames and numerical analyses of RC frame buildings. The features were found to be reasonable and can be used in machine-learning applications to identify deformation modes.