文献类型：期刊文献

英文题名：High-Rise Building Deformation Monitoring Based on Remote Wireless Sensor Network

作者：Yuan, Shengli[1]

第一作者：原胜利

通讯作者：Yuan, SL[1]

机构：[1]Xinxiang Univ, Sch Civil Engn & Architecture, Xinxiang 453000, Henan, Peoples R China

第一机构：新乡学院土木工程与建筑学院

通讯机构：[1]corresponding author), Xinxiang Univ, Sch Civil Engn & Architecture, Xinxiang 453000, Henan, Peoples R China.|[1107114]新乡学院土木工程与建筑学院;[11071]新乡学院;

年份：2021

卷号：21

期号：22

起止页码：25133-25141

外文期刊名：IEEE SENSORS JOURNAL

收录：;EI(收录号：20211310151081);Scopus(收录号：2-s2.0-85103263183);WOS:【SCI-EXPANDED(收录号:WOS:000717802500031)】；

基金：This work was supported by the Scientific and Technological innovation Fund of Xinxiang University through the Research on informatization construction monitoring technology of deep foundation Pit Project under Grant 15ZB14. The associate editor coordinating the review of this article and approving it for publication was Dr. Wei Wei.

语种：英文

外文关键词：Monitoring; Buildings; Temperature sensors; Wireless sensor networks; Temperature measurement; Strain; Sensor systems; Remote wireless sensor network; high-rise buildings; deformation monitoring; dynamic monitoring system

摘要：Deformation monitoring of high-rise buildings is necessary. Among them, foundation settlement is one of the most important factors of building deformation. This paper designs the layout of the high-rise building foundation settlement monitoring points and the monitoring method of the foundation settlement, designs and implements the above-mentioned remote wireless sensor network-based high-rise building foundation settlement dynamic early warning system of the lower computer hardware and software and the upper computer system. Analyzed the requirements of the system and designed the overall structure of the system. The functional analysis of remote wireless sensor network equipment, serial communication tools, and host computer system is done, and the whole working process of the dynamic monitoring system for the settlement of the foundation of high-rise buildings is introduced in detail. The system adopts the modular design idea, and the neural network SPKF method is proposed for the first time, and it is applied to the modeling and prediction of the nonlinear system of high-rise building deformation monitoring. This method solves the shortcomings of long training time of BP neural network, large dependence on initial value, and easy to fall into local extreme value. It also realizes the advantages of neural network with the ability to approximate arbitrary continuous functions and nonlinear mapping through SPKF. The results of calculation examples prove the feasibility and effectiveness of this idea and method.