Building is a major issue today because of our growing population, but also from an ecological perspective. To meet this challenge, it is advantageous to build buildings in wood rather than concrete. In this way, the desire to increase the height of these buildings is intensifying. However, building standards of these structures is not appropriate. But, wood is a complex material because of it has a large variation of parameters and is very sensitive to its environment which makes it difficult to study [1]. To fix this issue, we will present a method to study the linear dynamics of wooden building and estimate modal parameters of the structure without knowledge of material. First, a scaled-down timber building will be present and its modal analysis. Then we will estimate its dynamic parameters, the technique use for, adopt data assimilation methods as Extended Kalman Filter (EKF) [2] which will explain in the second section. Finally, the results from experiments will be submit and we will cite some limits and perspectives.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Modeling and Identification of Dynamic Behavior in Timber Structure

  • Layla Kordylas,
  • Franck Renaud,
  • Jean-Luc Dion

摘要

Building is a major issue today because of our growing population, but also from an ecological perspective. To meet this challenge, it is advantageous to build buildings in wood rather than concrete. In this way, the desire to increase the height of these buildings is intensifying. However, building standards of these structures is not appropriate. But, wood is a complex material because of it has a large variation of parameters and is very sensitive to its environment which makes it difficult to study [1]. To fix this issue, we will present a method to study the linear dynamics of wooden building and estimate modal parameters of the structure without knowledge of material. First, a scaled-down timber building will be present and its modal analysis. Then we will estimate its dynamic parameters, the technique use for, adopt data assimilation methods as Extended Kalman Filter (EKF) [2] which will explain in the second section. Finally, the results from experiments will be submit and we will cite some limits and perspectives.