Condition Assessment of Tower and Mast Structures Monitored within One Cluster under Changing Environments
Numerous communications and power towers are distributed around urban districts. To ensure the safety of tower and mast structures, an effective measurement is to establish a simple structural health monitoring (SHM) system for each tower structure to obtain continuous deformation data of all struct...
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Series: | Advances in Civil Engineering |
Online Access: | http://dx.doi.org/10.1155/2020/8820104 |
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doaj-b18f342fdc6948d6aae0fa0c4fb92a282020-11-30T09:11:24ZengHindawi LimitedAdvances in Civil Engineering1687-80861687-80942020-01-01202010.1155/2020/88201048820104Condition Assessment of Tower and Mast Structures Monitored within One Cluster under Changing EnvironmentsChangping Li0Xinteng Ma1Yang Liu2School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150001, ChinaSchool of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150001, ChinaSchool of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150001, ChinaNumerous communications and power towers are distributed around urban districts. To ensure the safety of tower and mast structures, an effective measurement is to establish a simple structural health monitoring (SHM) system for each tower structure to obtain continuous deformation data of all structures. However, there is little research focusing on evaluating the condition of tower and mast structures monitored within one cluster using deformation monitoring data. To address this issue, a condition assessment approach combining principal component analysis (PCA) with cross-validation is proposed in this study. The PCA-based method is applied to mitigate the influence of environmental temperature and speed load on the horizontal displacement monitoring data, and novelty detection based on cross-validation is adopted to evaluate the condition of all the tower and mast structures monitored within one cluster. Finally, the effectiveness of the proposed method is demonstrated using monitoring data obtained from actual tower and mast structures.http://dx.doi.org/10.1155/2020/8820104 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Changping Li Xinteng Ma Yang Liu |
spellingShingle |
Changping Li Xinteng Ma Yang Liu Condition Assessment of Tower and Mast Structures Monitored within One Cluster under Changing Environments Advances in Civil Engineering |
author_facet |
Changping Li Xinteng Ma Yang Liu |
author_sort |
Changping Li |
title |
Condition Assessment of Tower and Mast Structures Monitored within One Cluster under Changing Environments |
title_short |
Condition Assessment of Tower and Mast Structures Monitored within One Cluster under Changing Environments |
title_full |
Condition Assessment of Tower and Mast Structures Monitored within One Cluster under Changing Environments |
title_fullStr |
Condition Assessment of Tower and Mast Structures Monitored within One Cluster under Changing Environments |
title_full_unstemmed |
Condition Assessment of Tower and Mast Structures Monitored within One Cluster under Changing Environments |
title_sort |
condition assessment of tower and mast structures monitored within one cluster under changing environments |
publisher |
Hindawi Limited |
series |
Advances in Civil Engineering |
issn |
1687-8086 1687-8094 |
publishDate |
2020-01-01 |
description |
Numerous communications and power towers are distributed around urban districts. To ensure the safety of tower and mast structures, an effective measurement is to establish a simple structural health monitoring (SHM) system for each tower structure to obtain continuous deformation data of all structures. However, there is little research focusing on evaluating the condition of tower and mast structures monitored within one cluster using deformation monitoring data. To address this issue, a condition assessment approach combining principal component analysis (PCA) with cross-validation is proposed in this study. The PCA-based method is applied to mitigate the influence of environmental temperature and speed load on the horizontal displacement monitoring data, and novelty detection based on cross-validation is adopted to evaluate the condition of all the tower and mast structures monitored within one cluster. Finally, the effectiveness of the proposed method is demonstrated using monitoring data obtained from actual tower and mast structures. |
url |
http://dx.doi.org/10.1155/2020/8820104 |
work_keys_str_mv |
AT changpingli conditionassessmentoftowerandmaststructuresmonitoredwithinoneclusterunderchangingenvironments AT xintengma conditionassessmentoftowerandmaststructuresmonitoredwithinoneclusterunderchangingenvironments AT yangliu conditionassessmentoftowerandmaststructuresmonitoredwithinoneclusterunderchangingenvironments |
_version_ |
1715027954690424832 |