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Safety State Evaluation Method Based on Attribute Recognition Model for Ancient Timber Buildings

Author(s):



Medium: journal article
Language(s): English
Published in: Advances in Civil Engineering, , v. 2019
Page(s): 1-13
DOI: 10.1155/2019/3612535
Abstract:

To improve accuracy of safety state evaluation results for ancient timber buildings and to know the real state of the building, a safety grade evaluation model of ancient timber buildings is established based on attribute mathematic theory. From the perspective of macro, micro, qualitative, and quantitative, 22 factors may adversely affect the safety state of ancient timber building are considered in this model. First, evaluation system is established, and evaluation indexes are selected based on former study, seismic damage data, and Chinese current code about ancient timber buildings. In the evaluation system, whole building is divided into four parts, which are wood frame, enclosing wall, foundation, and plinth. Different parts contain different components. Every component has its own evaluation indexes. Second, based on the AHP and entropy method, the comprehensive empowering method is used to determine the weights of the indexes. Third, the attribute recognition model is established to identify the safety grade of components or units. Fourth, based on the evaluation results of components, safety grade of units is identified. Then, safety degree of the entire building is determined by the minimum safety grade of units. At last, the model is applied to the “Liben hall” in village Siping, Zhejiang province, China, and the assessment results are consistent with the results of damage identification.

Copyright: © 2019 Junhong Huan et al.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10310153
  • Published on:
    05/03/2019
  • Last updated on:
    02/06/2021
 
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