Search for Author, Title, Keyword
RESEARCH PAPER
Effective sensor placement based on a VIKOR method considering common cause failure in the presence of epistemic uncertainty
,
 
,
 
 
 
 
More details
Hide details
1
School of Information Engineering, Nanchang University, Nanchang, 330031, P. R. China
 
 
Publication date: 2021-06-30
 
 
Eksploatacja i Niezawodność – Maintenance and Reliability 2021;23(2):253-262
 
HIGHLIGHTS
  • A VIKOR method is proposed to choose the possible sensor locations.
  • A sensor model is presented by using a priority AND gate in sensor placement.
  • CCF has an incredible influence on the reliabilitybased sensor placement method.
KEYWORDS
ABSTRACT
Owing to expensive cost and restricted structure, limited sensors are allowed to install in modern systems to monitor the working state, which can improve their availability. Therefore, an effective sensor placement method is presented based on a VIKOR algorithm considering common cause failure (CCF) under epistemic uncertainty in this paper. Specifically, a dynamic fault tree (DFT) is developed to build a fault model to simulate dynamic fault behaviors and some reliability indices are calculated using a dynamic evidence network (DEN). Furthermore, a VIKOR method is proposed to choose the possible sensor locations based on these indices. Besides, a sensor model is introduced by using a priority AND gate (PAND) to describe the failure sequence between a sensor and a component. All placement schemes can be enumerated when the number of sensors is given, and the largest system reliability is the best alternative among the placement schemes. Finally, a case study shows that CCF has some influence on sensor placement and cannot be neglected in the reliabilitybased sensor placement.
REFERENCES (44)
1.
Acuña-Soto CM, Liern V, Pérez-Gladish B. A VIKOR-based approach for the ranking of mathematical instructional videos. Management Decision 2019; 57(2): 501-522, http://doi.org/10.1108/md-03-2....
 
2.
Assaf T, Dugan JB. Diagnosis based on reliability analysis using monitors and sensors. Reliability Engineering & System Safety 2008; 93(4): 509-521, http://doi.org/10.1016/j.ress.....
 
3.
Błachowski B, Świercz A, Ostrowski M, Tauzowski P, Olaszek P, Jankowski Ł. Convex relaxation for efficient sensor layout optimization in large‐scale structures subjected to moving loads. Computer-Aided Civil and Infrastructure Engineering 2020; 35(10): 1085-1100, http://doi.org/10.1111/mice.12....
 
4.
Chow HM, Lam HF, Yin T, Au SK. Optimal sensor configuration of a typical transmission tower for the purpose of structural model updating. Structural Control and Health Monitoring 2011; 18(3): 305-320, http://doi.org/10.1002/stc.372.
 
5.
Dai G B, Ji G Y. Structure of Large Ground Modal Test Node Selecting and Optimizing Method Research. Journal of Vibration, Measurement & Diagnosis 2017; 37(05): 984-989, http://doi.org/10.16450/j.cnki....
 
6.
Dempster A P. Upper and lower probabilities induced by a multivalued mapping. Classic works of the Dempster-Shafer theory of belief functions 2008; 57-72, http://doi.org/10.1007/978-3-5....
 
7.
Duan R, Lin Y, Feng T. Optimal Sensor Placement Based on System Reliability Criterion Under Epistemic Uncertainty. IEEE Access 2018; 6: 57061-57072, http://doi.org/10.1109/access.....
 
8.
Duan R, Lin Y, Zeng Y. Fault diagnosis for complex systems based on reliability analysis and sensors data considering epistemic uncertainty. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2018; 20(4): 558-566, http://doi.org/10.17531/ein.20....
 
9.
Duan R, Ou D, Dong D, Zhou H. Optimal sensor placement for fault diagnosis based on diagnosis cost specifications. Journal of Computational Information Systems 2011; 7(9): 3253-3260,.
 
10.
Dugan J B, Bavuso S J, Boyd M A. Dynamic fault-tree models for fault-tolerant computer systems. IEEE Transactions on reliability 1992; 42(3): 363-377, http://doi.org/10.1109/24.1598....
 
11.
Feng T, Duan R, Lin Y, Zeng Y. Optimal sensor placement based on multiattribute decision-making considering the common cause failure. Proceedings of the Institution of Mechanical Engineers, Part C Journal of Mechanical Engineering Science 2019; 233(19/20): 7170-7182, http://doi.org/10.1177/0954406....
 
12.
Gomes GF, Pereira JVP. Sensor placement optimization and damage identification in a fuselage structure using inverse modal problem and firefly algorithm. Evolutionary Intelligence 2020, http://doi.org/10.1007/s12065-....
 
13.
Han X, Yin X, Zhang Z. Application of fault tree analysis method in reliability analysis of substation communication system. Power System Technology 2004.
 
14.
He C, Xing J, Li J, Yang Q, Wang R, Zhang X. A New Optimal Sensor Placement Strategy Based on Modified Modal Assurance Criterion and Improved Adaptive Genetic Algorithm for Structural Health Monitoring. Mathematical Problems in Engineering 2015; 2015: 1-10, http://doi.org/10.1155/2015/62....
 
15.
Kammer DC. Sensor placement for on-orbit modal identification and correlation of large space structures. Journal of Guidance, Control, and Dynamics 1991; 14(2): 251-259, http://doi.org/ 0.2514/3.20635.
 
16.
Kammer DC, Tinker ML. Optimal placement of triaxial accelerometers for modal vibration tests. Mechanical Systems and Signal Processing 2004; 18(1): 29-41, doi:10.1016/s0888-3270(03)00017-7.
 
17.
Kančev D, Čepin M. A new method for explicit modelling of single failure event within different common cause failure groups. Reliability Engineering & System Safety 2012; 103: 84-93, http://doi.org/10.1016/j.ress.....
 
18.
Kim T, Youn BD, Oh H. Development of a stochastic effective independence (SEFI) method for optimal sensor placement under uncertainty. Mechanical Systems and Signal Processing 2018; 111: 615-627, http://doi.org/10.1016/j.ymssp....
 
19.
Li Z Q, Xu T X, An J, Fu L Y, Gu J Y. Common cause failure modeling for redundant system based on dynamic Bayesian network. Chinese Journal of Scientific Instrument 2018; 39(3): 190-198, http://doi.org/10.19650/j.cnki....
 
20.
Li Z Q, Xu T X, Gu J Y, Liu Y D. Review on Research on Dependent Failure Analysis of Complex Systems. Failure Analysis and Prevention 2017; 12(2): 130-136.
 
21.
Mi J, Li Y-F, Beer M, Broggi M, Cheng Y. Importance measure of probabilistic common cause failures under system hybrid uncertainty based on bayesian network. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2020; 22(1): 112–120, http://doi.org/10.17531/ein.20....
 
22.
Mi J, Li Y-F, Peng W, Huang H-Z. Reliability Analysis of Complex Multi-state System with Common Cause Failure Based on DS Evidence Theory and Bayesian Network. Recent Advances in Multi-state Systems Reliability. 2018: 19-38, http://doi.org/10.1007/978-3-3....
 
23.
Mi J, Li Y-F, Peng W, Huang H-Z. Reliability analysis of complex multi-state system with common cause failure based on evidential networks. Reliability Engineering & System Safety 2018; 174: 71-81, http://doi.org/10.1016/j.ress.....
 
24.
Papadimitriou C, Lombaert G. The effect of prediction error correlation on optimal sensor placement in structural dynamics. Mechanical Systems and Signal Processing 2012; 28: 105-127, http://doi.org/10.1016/j.ymssp....
 
25.
Pitchaimanickam B, Murugaboopathi G. A hybrid firefly algorithm with particle swarm optimization for energy efficient optimal cluster head selection in wireless sensor networks. Neural Computing and Applications 2020; 32(12): 7709-7723,.
 
26.
Salazar JC, Weber P, Nejjari F, Sarrate R, Theilliol D. System reliability aware Model Predictive Control framework. Reliability Engineering & System Safety 2017; 167: 663-672, http://doi.org/10.1016/j.ress.....
 
27.
Salehpour-Oskouei F, Pourgol-Mohammad M. Fault Diagnosis Improvement Using Dynamic Fault Model in Optimal Sensor Placement: A Case Study of Steam Turbine. Quality and Reliability Engineering International 2017; 33(3): 531-541, http://doi.org/10.1002/qre.203....
 
28.
Salehpour-Oskouei F, Pourgol-Mohammad M. Sensor placement determination in system health monitoring process based on dual information risk and uncertainty criteria. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 2017; 232(1): 65-81, http://doi.org/10.1177/1748006....
 
29.
Sallak M, Schon W, Aguirre F. Extended Component Importance Measures Considering Aleatory and Epistemic Uncertainties. IEEE Transactions on Reliability 2013; 62(1): 49-65, http://doi.org/10.1109/tr.2013....
 
30.
Shafer G. A mathematical theory of evidence. Princeton University Press, 1976.
 
31.
Shan J, Shi W, Lu X. Model-Reference Health Monitoring of Hysteretic Building Structure Using Acceleration Measurement with Test Validation. Computer-Aided Civil and Infrastructure Engineering 2016; 31(6): 449-464, http://doi.org/10.1111/mice.12....
 
32.
Song Y, Mi J, Cheng Y, Bai L, Wang X. Application of discrete‐time Bayesian network on reliability analysis of uncertain system with common cause failure. Quality and Reliability Engineering International 2018; 35(4): 1025-1045, http://doi.org/10.1002/qre.244....
 
33.
Steffelbauer DB, Fuchs-Hanusch D. Efficient Sensor Placement for Leak Localization Considering Uncertainties. Water Resources Management 2016; 30(14): 5517-5533, http://doi.org/10.1007/s11269-....
 
34.
Sun H, Yao W. Comments on methods for ranking interval numbers. Journal of Systems Engineering 2010; 25(3): 304-312.
 
35.
Xie X, Zhou Q, Hou D, Zhang H. Compressed sensing based optimal sensor placement for leak localization in water distribution networks. Journal of Hydroinformatics 2018; 20(6): 1286-1295, http://doi.org/10.2166/hydro.2....
 
36.
Yang C, Ma R, Ma R. Optimal Sensor Placement for Modal Identification in Multirotary-Joint Solar Power Satellite. IEEE Sensors Journal 2020; 20(13): 7337-7346, http://doi.org/10.1109/jsen.20....
 
37.
Yang C, Zhang X, Huang X, Cheng Z, Zhang X, Hou X. Optimal sensor placement for deployable antenna module health monitoring in SSPS using genetic algorithm. Acta Astronautica 2017; 140: 213-224, http://doi.org/10.1016/j.actaa....
 
38.
Yi T-H, Li H-N, Wang C-W. Multiaxial sensor placement optimization in structural health monitoring using distributed wolf algorithm. Structural Control and Health Monitoring 2016; 23(4): 719-734, http://doi.org/10.1002/stc.180....
 
39.
Yu G, Du Y, Yan L, Ren F. Stress-strength interference-based importance for series systems considering common cause failure. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22(2): 241-252, http://doi.org/10.17531/ein.20....
 
40.
Zarei E, Azadeh A, Khakzad N, Aliabadi MM, Mohammadfam I. Dynamic safety assessment of natural gas stations using Bayesian network. Journal of Hazardous Materials 2017; 321: 830-840, http://doi.org/10.1016/j.jhazm....
 
41.
Zhang Q, Zheng Y, Zhao M, Qi J. Leakage Zone Identification in Large-Scale Water Distribution Systems Using Multiclass Support Vector Machines. Journal of Water Resources Planning & Management 2016; 142(11): 04016042, http://doi.org/10.1061/(ASCE)W....
 
42.
Zhang Y, Yang J. Reliability Analysis on ATP System of CTCS-3 Based on Dynamic Bayesian Network. Journal of the China Railway Society 2017; 39(7): 79-86, http://doi.org/10.3969/j.issn.....
 
43.
Zubair M, Amjad QMN. Calculation and updating of Common Cause Failure unavailability by using alpha factor model. Annals of Nuclear Energy 2016; 90: 106-114, http://doi.org/10.1016/j.anuce....
 
44.
Zuo L, Xiahou T, Liu Y. Evidential network-based failure analysis for systems suffering common cause failure and model parameter uncertainty. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 2018; 233(6): 2225-2235, http://doi.org/10.1177/0954406....
 
 
CITATIONS (2):
1.
The Influence of Halide Ion Substitution on Energy Structure and Luminescence Efficiency in CeBr2I and CeBrI2 Crystals
Krzysztof Przystupa, Yaroslav Chornodolskyy, Jarosław Selech, Vladyslav Karnaushenko, Taras Demkiv, Orest Kochan, Stepan Syrotyuk, Anatolii Voloshinovskii
Materials
 
2.
A reliability evaluation method for complex systems based on the editable GSPN and adaptive Monte Carlo simulation
Yining Zeng, Youchao Sun, Tao Xu, Siyu Su
Systems Engineering
 
eISSN:2956-3860
ISSN:1507-2711
Journals System - logo
Scroll to top