A Novel Risk-Based Prioritization Approach for Wireless Sensor Network Deployment in Pipeline Networks

被引:0
作者
Yi, Xiaojian [1 ,2 ]
Hou, Peng [1 ]
Dong, Haiping [1 ]
机构
[1] Beijing Inst Technol, Sch Mechatron Engn, Beijing 100081, Peoples R China
[2] Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
关键词
wireless sensor network deployment; pipeline network; risk-based prioritization; inhomogeneous Poisson point process; condition monitoring; coverage problem; SPATIAL AUTOCORRELATION; INSPECTION STRATEGIES; TARGET COVERAGE; MAINTENANCE;
D O I
10.3390/en13061512
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
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.
引用
收藏
页数:15
相关论文
共 47 条
[1]  
Aguiar E.F. K., 2015, J. Environ. Prot. (Irvine, V06, P173, DOI DOI 10.4236/JEP.2015.62019
[2]   Location prediction optimisation in WSNs using Kriging interpolation [J].
Ali, Arshad ;
Ikpehai, Augustine ;
Adebisi, Bamidele ;
Mihaylova, Lyudmila .
IET WIRELESS SENSOR SYSTEMS, 2016, 6 (03) :74-81
[3]   Risk-based maintenance - Techniques and applications [J].
Arunraj, N. S. ;
Maiti, J. .
JOURNAL OF HAZARDOUS MATERIALS, 2007, 142 (03) :653-661
[4]   Deployment Strategies in the Wireless Sensor Networks: Systematic Literature Review, Classification, and Current Trends [J].
Aznoli, Fariba ;
Navimipour, Nima Jafari .
WIRELESS PERSONAL COMMUNICATIONS, 2017, 95 (02) :819-846
[5]   Using AHP in determining the prior distributions on gas pipeline failures in a robust Bayesian approach [J].
Cagno, E ;
Caron, F ;
Mancini, M ;
Ruggeri, F .
RELIABILITY ENGINEERING & SYSTEM SAFETY, 2000, 67 (03) :275-284
[6]  
Calixto E., 2015, SAFETY RELIABILITY C, P3425
[7]  
Cardei M, 2005, IEEE INFOCOM SER, P1976
[8]  
Carrapetta J., 2010, THESIS
[9]  
Case Studies in Spatial Point Process Modeling, 2006, CAS STUD SPAT POINT, V101, P17
[10]  
Changqing Wang, 2011, 2011 IEEE 13th International Conference on Communication Technology (ICCT), P938, DOI 10.1109/ICCT.2011.6158017