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タイトル: A Bayesian approach for vibration-based long-term bridge monitoring to consider environmental and operational changes
著者: Kim, Chul-Woo  kyouindb  KAKEN_id
Morita, Tomoaki
Oshima, Yoshinobu
Sugiura, Kunitomo  kyouindb  KAKEN_id
著者名の別形: 金, 哲佑
キーワード: long-term bridge monitoring
Bayesian regression
temperature
vehicle weight
vibration
発行日: 25-Feb-2015
出版者: Techno-Press
誌名: Smart Structures and Systems
巻: 15
号: 2
開始ページ: 395
終了ページ: 408
抄録: This study aims to propose a Bayesian approach to consider changes in temperature and vehicle weight as environmental and operational factors for vibration-based long-term bridge health monitoring. The Bayesian approach consists of three steps: step 1 is to identify damage-sensitive features from coefficients of the auto-regressive model utilizing bridge accelerations; step 2 is to perform a regression analysis of the damage-sensitive features to consider environmental and operational changes by means of the Bayesian regression; and step 3 is to make a decision on the bridge health condition based on residuals, differences between the observed and predicted damage-sensitive features, utilizing 95% confidence interval and the Bayesian hypothesis testing. Feasibility of the proposed approach is examined utilizing monitoring data on an in-service bridge recorded over a one-year period. Observations through the study demonstrated that the Bayesian regression considering environmental and operational changes led to more accurate results than that without considering environmental and operational changes. The Bayesian hypothesis testing utilizing data from the healthy bridge, the damage probability of the bridge was judged as no damage.
著作権等: 発行元の許可を得て掲載しています。This is not the published version. Please cite only the published version. この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。
URI: http://hdl.handle.net/2433/236010
DOI(出版社版): 10.12989/sss.2015.15.2.395
出現コレクション:学術雑誌掲載論文等

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