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...

Full description

Bibliographic Details
Main Authors: Changping Li, Xinteng Ma, Yang Liu
Format: Article
Language:English
Published: Hindawi Limited 2020-01-01
Series:Advances in Civil Engineering
Online Access:http://dx.doi.org/10.1155/2020/8820104
id doaj-b18f342fdc6948d6aae0fa0c4fb92a28
record_format Article
spelling 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