scholarly journals Effective sensor placement based on a VIKOR method considering common cause failure in the presence of epistemic uncertainty

2021 ◽  
Vol 23 (2) ◽  
pp. 253-262
Author(s):  
Rong-Xing Duan ◽  
Jie-Jun He ◽  
Tao Feng ◽  
Shu-Juan Huang ◽  
Li Chen
Keyword(s):  
System Reliability ◽  
Epistemic Uncertainty ◽  
Sensor Placement ◽  
Vikor Method ◽  
Common Cause ◽  
Reliability Indices ◽  
Common Cause Failure ◽  
Dynamic Fault Tree ◽  
Sensor Model

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.

Optimal sensor placement based on multiattribute decision-making considering the common cause failure

2019 ◽  
Vol 233 (19-20) ◽  
pp. 7170-7182 ◽  
Author(s):  
Tao Feng ◽  
Rongxing Duan ◽  
Yanni Lin ◽  
Yining Zeng
Keyword(s):  
Decision Making ◽  
Sensor Placement ◽  
Fault Tree ◽  
Optimal Placement ◽  
Decision Matrix ◽  
Optimal Sensor Placement ◽  
Common Cause ◽  
Common Cause Failure ◽  
Dynamic Fault Tree ◽  
The Common

A new optimal sensor placement is developed to improve the efficiency of fault diagnosis based on multiattribute decision-making considering the common cause failure. The optimal placement scheme is selected based on the reliability of the top event on condition that the number of sensors is preset. Specifically, a β-factor model is introduced to deal with the common cause failure, and dynamic fault tree is used to describe the dynamic failure behaviors. Besides, a dynamic fault tree is converted into a dynamic Bayesian network to calculate the reliability parameters, which construct the decision matrix. Furthermore, an efficient TOPSIS algorithm is adopted to determine the potential locations of sensors. In addition, a diagnostic sensor model is developed to take into account the failure sequence between a sensor and a component using a priority AND gate, and the failure probability of the top event for all sensor placement scenarios is calculated to determine the optimal sensor placement. Finally, a case is provided to prove that the common cause failure has made a considerable impact on the sensor placement.

Optimal fault diagnosis strategy for complex systems considering common cause failure under epistemic uncertainty

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rongxing Duan ◽  
Shujuan Huang ◽  
Jiejun He
Keyword(s):  
Fault Diagnosis ◽  
Complex Systems ◽  
Reliability Analysis ◽  
Epistemic Uncertainty ◽  
Fault Tree ◽  
Common Cause ◽  
Content Type ◽  
Common Cause Failure ◽  
Dynamic Fault Tree ◽  
Evidence Network

Purpose This paper aims to deal with the problems such as epistemic uncertainty, common cause failure (CCF) and dynamic fault behaviours that arise in complex systems and develop an effective fault diagnosis method to rapidly locate the fault when these systems fail. Design/methodology/approach First, a dynamic fault tree model is established to capture the dynamic failure behaviours and linguistic term sets are used to obtain the failure rate of components in complex systems to deal with the epistemic uncertainty. Second, a β factor model is used to construct a dynamic evidence network model to handle CCF and some parameters obtained by reliability analysis are used to build the fault diagnosis decision table. Finally, an improved Vlsekriterijumska Optimizacija I Kompromisno Resenje algorithm is developed to obtain the optimal diagnosis sequence, which can locate the fault quickly, reduce the maintenance cost and improve the diagnosis efficiency. Findings In this paper, a new optimal fault diagnosis strategy of complex systems considering CCF under epistemic uncertainty is presented based on reliability analysis. Dynamic evidence network is easy to carry out the quantitative analysis of dynamic fault tree. The proposed diagnosis algorithm can determine the optimal fault diagnosis sequence of complex systems and prove that CCF should not be ignored in fault diagnosis. Originality/value The proposed method combines the reliability theory with multiple attribute decision-making methods to improve the diagnosis efficiency.

Uncertainty analysis of common cause failure in safety instrumented systems

2011 ◽  
Vol 225 (4) ◽  
pp. 450-460 ◽  
Author(s):  
W Mechri ◽  
C Simon ◽  
K Ben Othman
Keyword(s):  
Fuzzy Numbers ◽  
Epistemic Uncertainty ◽  
Monte Carlo Sampling ◽  
Fault Trees ◽  
Common Cause ◽  
Common Cause Failure ◽  
On Demand ◽  
Safety Integrity Level ◽  
Imperfect Knowledge ◽  
The Common

This paper analyses the problem of epistemic uncertainty in assessing the performance of safety instrumented systems (SIS) using fault trees. The imperfect knowledge concerns the common cause failure (CCF) involved in the SIS in low demand mode. The point-valued CCF factors are replaced by fuzzy numbers, allowing experts to express their uncertainty about the CCF values. This paper shows how these uncertainties propagate through the fault tree and how this induces an uncertainty to the values of the SIS failure probability on demand and to the safety integrity level of the SIS. For the sake of verification and comparison, and to show the exactness of the approach, a Monte Carlo sampling approach is proposed, where by a uniform or triangular second-order probability distribution of CCF factors is considered.

Reliability analysis for complex systems based on generalized stochastic petri nets and EDA approach considering common cause failure

2019 ◽  
Vol 37 (5) ◽  
pp. 1513-1530 ◽  
Author(s):  
Yining Zeng ◽  
Rongxing Duan ◽  
Shujuan Huang ◽  
Tao Feng
Keyword(s):  
Complex Systems ◽  
Reliability Analysis ◽  
Evaluation Method ◽  
Stochastic Petri Nets ◽  
Importance Measure ◽  
Dynamic Failure ◽  
Common Cause ◽  
Content Type ◽  
Common Cause Failure ◽  
Dynamic Fault Tree

Purpose This paper aims to deal with the problems of failure dependence and common cause failure (CCF) that arise in reliability analysis of complex systems. Design/methodology/approach Firstly, a dynamic fault tree (DFT) is used to capture the dynamic failure behaviours and converted into an equivalent generalized stochastic petri net (GSPN) for quantitative analysis. Secondly, an efficient decomposition and aggregation (EDA) theory is combined with GSPN to deal with the CCF problem, which exists in redundant systems. Finally, Birnbaum importance measure (BIM) is calculated based on the EDA approach and GSPN model, and it is used to take decisions for system improvement and fault diagnosis. Findings In this paper, a new reliability evaluation method for dynamic systems subject to CCF is presented based on the DFT analysis and the GSPN model. The GSPN model is easy to capture dynamic failure behaviours of complex systems, and the movement of tokens in the GSPN model represent the changes in the state of the systems. The proposed method takes advantage of the GSPN model and incorporates the EDA method into the GSPN, which simplifies the reliability analysis process. Meanwhile, simulation results under different conditions show that CCF has made a considerable impact on reliability analysis for complex systems, which indicates that the CCF should not be ignored in reliability analysis. Originality/value The proposed method combines the EDA theory with the GSPN model to improve the efficiency of the reliability analysis.

Design and Development of HTR-PM Reactor Protection System

2013 ◽  
Author(s):  
Duo Li ◽  
Huasheng Xiong ◽  
Chao Guo
Keyword(s):  
High Temperature ◽  
Power Plant ◽  
System Reliability ◽  
Nuclear Power ◽  
Protection System ◽  
Common Cause ◽  
Common Cause Failure ◽  
Plant Reactor ◽  
Reactor Protection System ◽  
High Temperature Gas

High Temperature gas-cooled Reactor-Pebble bed Module (HTR-PM) Reactor Protection System (RPS) is a dedicated system to be designed and developed according to HTR-PM Nuclear Power Plant reactor protection specifications. HTR-PM RPS has the framework of four redundant channels and has two independent and diverse subsystem x and subsystem y to perform different protection functions, which would decrease the potential common cause failure caused by software and increase the system reliability.

The Case Study for Diversity in Nuclear Plant Instrument and Control System

2011 ◽  
Vol 383-390 ◽  
pp. 4163-4168
Author(s):  
Tao Fang ◽  
Jin Song Hu ◽  
Dao Gang Lu ◽  
Zhi Yin Liu
Keyword(s):  
Control System ◽  
Nuclear Plant ◽  
Function Structure ◽  
Tree Analysis ◽  
Common Cause ◽  
Common Cause Failure ◽  
Actuation System ◽  
Failure Tree ◽  
And Control

This paper through describing the comparison between LingAo Phrase II ATWT and Tomari DAS (Diverse Actuation System) in some aspects which including function, structure, and so on. Through the comparison, the author finds the biggest difference between the systems is the manual analog devices are used in ATWT. And the author proves the full digital control system’s performance is used to defense the CCF (Common Cause Failure). Especially the Controller be detailed analyzed by FTA (Failure Tree Analysis) and unavailability, because of the controller’s important. At last the author proposes better solutions for coping with the requirement of the Defense in CCF.

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