A Computing Model for Quantifying the Value of Structural Health Monitoring Information in Bridge Engineering

A Computing Model for Quantifying the Value of Structural Health Monitoring Information in Bridge Engineering

Structural health monitoring system can provide valuable information for improving decision-making process in maintenance and management of bridges. However, managers usually lack understanding of value of structural health monitoring information. This paper developed a computing model for quantifyi...

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Main Authors: Baoquan Cheng, Lijie Wang, Jianling Huang, Xu Shi, Xiaodong Hu, Huihua Chen
Format: Article
Language:English
Published: Hindawi Limited 2020-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2020/8260909
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spelling doaj-ddbff8a903a1460fb5e2b839d57f2eea2020-11-25T03:41:15ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472020-01-01202010.1155/2020/82609098260909A Computing Model for Quantifying the Value of Structural Health Monitoring Information in Bridge EngineeringBaoquan Cheng0Lijie Wang1Jianling Huang2Xu Shi3Xiaodong Hu4Huihua Chen5School of Civil Engineering, Central South University, Changsha, Hunan 410083, ChinaDepartment of Architecture, Shijiazhuang Institute of Railway Technology, Shijiazhuang, Hebei 050041, ChinaSchool of Civil Engineering, Central South University, Changsha, Hunan 410083, ChinaCollege of Optoelectronic Engineering, Chongqing University, Chongqing 400044, ChinaSchool of Civil Engineering, Central South University, Changsha, Hunan 410083, ChinaSchool of Civil Engineering, Central South University, Changsha, Hunan 410083, ChinaStructural health monitoring system can provide valuable information for improving decision-making process in maintenance and management of bridges. However, managers usually lack understanding of value of structural health monitoring information. This paper developed a computing model for quantifying the value of structural health monitoring information based on Bayesian theory. Then, the model was demonstrated and validated using a simple case and the key factors (i.e., system accuracy, reparation cost, prior probability of structural failure, and manager’s behavior pattern) influencing the value of structural health monitoring information were identified and discussed. Findings from this study help to answer the question of whether a structural health monitoring system should be installed and run, thus enriching the knowledge body of structural health monitoring.http://dx.doi.org/10.1155/2020/8260909
collection DOAJ
language English
format Article
sources DOAJ
author Baoquan Cheng
Lijie Wang
Jianling Huang
Xu Shi
Xiaodong Hu
Huihua Chen
spellingShingle Baoquan Cheng
Lijie Wang
Jianling Huang
Xu Shi
Xiaodong Hu
Huihua Chen
A Computing Model for Quantifying the Value of Structural Health Monitoring Information in Bridge Engineering
Mathematical Problems in Engineering
author_facet Baoquan Cheng
Lijie Wang
Jianling Huang
Xu Shi
Xiaodong Hu
Huihua Chen
author_sort Baoquan Cheng
title A Computing Model for Quantifying the Value of Structural Health Monitoring Information in Bridge Engineering
title_short A Computing Model for Quantifying the Value of Structural Health Monitoring Information in Bridge Engineering
title_full A Computing Model for Quantifying the Value of Structural Health Monitoring Information in Bridge Engineering
title_fullStr A Computing Model for Quantifying the Value of Structural Health Monitoring Information in Bridge Engineering
title_full_unstemmed A Computing Model for Quantifying the Value of Structural Health Monitoring Information in Bridge Engineering
title_sort computing model for quantifying the value of structural health monitoring information in bridge engineering
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2020-01-01
description Structural health monitoring system can provide valuable information for improving decision-making process in maintenance and management of bridges. However, managers usually lack understanding of value of structural health monitoring information. This paper developed a computing model for quantifying the value of structural health monitoring information based on Bayesian theory. Then, the model was demonstrated and validated using a simple case and the key factors (i.e., system accuracy, reparation cost, prior probability of structural failure, and manager’s behavior pattern) influencing the value of structural health monitoring information were identified and discussed. Findings from this study help to answer the question of whether a structural health monitoring system should be installed and run, thus enriching the knowledge body of structural health monitoring.
url http://dx.doi.org/10.1155/2020/8260909
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