A Novel Risk-Based Prioritization Approach for Wireless Sensor Network Deployment in Pipeline Networks
In the face of increased spatial distribution and a limited budget, monitoring critical regions of pipeline network is looked upon as an important part of condition monitoring through wireless sensor networks. To achieve this aim, it is necessary to target critical deployed regions rather than the a...
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Online Access: | https://www.mdpi.com/1996-1073/13/6/1512 |
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doaj-dafefac90f7c4eb5bc17d9103a08feb02020-11-25T01:28:23ZengMDPI AGEnergies1996-10732020-03-01136151210.3390/en13061512en13061512A Novel Risk-Based Prioritization Approach for Wireless Sensor Network Deployment in Pipeline NetworksXiaojian Yi0Peng Hou1Haiping Dong2School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, ChinaIn the face of increased spatial distribution and a limited budget, monitoring critical regions of pipeline network is looked upon as an important part of condition monitoring through wireless sensor networks. To achieve this aim, it is necessary to target critical deployed regions rather than the available deployed ones. Unfortunately, the existing approaches face grave challenges due to the vulnerability of identification to human biases and errors. Here, we have proposed a novel approach to determine the criticality of different deployed regions by ranking them based on risk. The probability of occurrence of the failure event in each deployed region is estimated by spatial statistics to measure the uncertainty of risk. The severity of risk consequence is measured for each deployed region based on the total cost caused by failure events. At the same time, hypothesis testing is used before the application of the proposed approach. By validating the availability of the proposed approach, it provides a strong credible basis and the falsifiability for the analytical conclusion. Finally, a case study is used to validate the feasibility of our approach to identify the critical regions. The results of the case study have implications for understanding the spatial heterogeneity of the occurrence of failure in a pipeline network. Meanwhile, the spatial distribution of risk uncertainty is a useful priori knowledge on how to guide the random deployment of wireless sensors, rather than adopting the simple assumption that each sensor has an equal likelihood of being deployed at any location.https://www.mdpi.com/1996-1073/13/6/1512wireless sensor network deploymentpipeline networkrisk-based prioritizationinhomogeneous poisson point processcondition monitoringcoverage problem |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xiaojian Yi Peng Hou Haiping Dong |
spellingShingle |
Xiaojian Yi Peng Hou Haiping Dong A Novel Risk-Based Prioritization Approach for Wireless Sensor Network Deployment in Pipeline Networks Energies wireless sensor network deployment pipeline network risk-based prioritization inhomogeneous poisson point process condition monitoring coverage problem |
author_facet |
Xiaojian Yi Peng Hou Haiping Dong |
author_sort |
Xiaojian Yi |
title |
A Novel Risk-Based Prioritization Approach for Wireless Sensor Network Deployment in Pipeline Networks |
title_short |
A Novel Risk-Based Prioritization Approach for Wireless Sensor Network Deployment in Pipeline Networks |
title_full |
A Novel Risk-Based Prioritization Approach for Wireless Sensor Network Deployment in Pipeline Networks |
title_fullStr |
A Novel Risk-Based Prioritization Approach for Wireless Sensor Network Deployment in Pipeline Networks |
title_full_unstemmed |
A Novel Risk-Based Prioritization Approach for Wireless Sensor Network Deployment in Pipeline Networks |
title_sort |
novel risk-based prioritization approach for wireless sensor network deployment in pipeline networks |
publisher |
MDPI AG |
series |
Energies |
issn |
1996-1073 |
publishDate |
2020-03-01 |
description |
In the face of increased spatial distribution and a limited budget, monitoring critical regions of pipeline network is looked upon as an important part of condition monitoring through wireless sensor networks. To achieve this aim, it is necessary to target critical deployed regions rather than the available deployed ones. Unfortunately, the existing approaches face grave challenges due to the vulnerability of identification to human biases and errors. Here, we have proposed a novel approach to determine the criticality of different deployed regions by ranking them based on risk. The probability of occurrence of the failure event in each deployed region is estimated by spatial statistics to measure the uncertainty of risk. The severity of risk consequence is measured for each deployed region based on the total cost caused by failure events. At the same time, hypothesis testing is used before the application of the proposed approach. By validating the availability of the proposed approach, it provides a strong credible basis and the falsifiability for the analytical conclusion. Finally, a case study is used to validate the feasibility of our approach to identify the critical regions. The results of the case study have implications for understanding the spatial heterogeneity of the occurrence of failure in a pipeline network. Meanwhile, the spatial distribution of risk uncertainty is a useful priori knowledge on how to guide the random deployment of wireless sensors, rather than adopting the simple assumption that each sensor has an equal likelihood of being deployed at any location. |
topic |
wireless sensor network deployment pipeline network risk-based prioritization inhomogeneous poisson point process condition monitoring coverage problem |
url |
https://www.mdpi.com/1996-1073/13/6/1512 |
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