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Issue title: Special section: Artificial Intelligence driven Big Data Analytics for COVID-19
Guest editors: Xiaolong Li
Article type: Research Article
Authors: Qiuling, Zheng | Ke, Yang | Qiang, Xu | Chenglong, Zhang; * | Liguang, Wang
Affiliations: Jilin Jianzhu University, Changchun, Jilin, China
Correspondence: [*] Corresponding author. Zhang Chenglong, Jilin Jianzhu University, Changchun 130118, Jilin, China. E-mail: [email protected].
Abstract: Under the influence of novel corona virus pneumonia, the staff are controlled. Therefore, it is a difficult problem to measure the parameters of wood structure building on site. The measurement error of traditional wood structure parameters in complex environment is large, so an efficient and accurate measurement and recognition method is needed. In this paper, a method combining random decrement method and ITD method is proposed to measure the frequency, damping ratio and other structural dynamic parameters of ancient building timber structure under crowd random load excitation. In this paper, the frequency and damping ratio of the typical ancient building timber structure are predicted by using the artificial neural network model trained by the known data. The experimental results show that the population density has a great influence on the measurement of the dynamic parameters of the wooden structure of ancient buildings. Using this method, combined with the long-term monitoring data of temperature and humidity, the influence of various environmental factors on the dynamic characteristics of the structure can be analyzed. This provides data support for structural damage identification and health monitoring.
Keywords: Artificial neural network (ANN), ITD method, population distribution density, dynamic characteristics, COVID-19
DOI: 10.3233/JIFS-189268
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 6, pp. 8723-8729, 2020
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