Belief Universal Generating Function Analysis of Multi-State Systems Under Epistemic Uncertainty and Common Cause Failures

Mi, Jinhua; Li, Yanfeng; Liu, Yu; Yang, Yun; Huang, Hong‐Zhong

doi:10.1109/tr.2015.2419620

Cited by 68 publications

(38 citation statements)

References 37 publications

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“…If the system in the same sort adds one parallel component, the reliability can refer to equation (2). Then we can get the rough reliability one of all systems--calculation method one.…”

Section: Process Of the MC Modelmentioning

confidence: 99%

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Reliability Evaluation and Selection in Multi-State System

Hu¹,

Liu²,

Hong-jie³

2018

dteees

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The multi-state system is an essential tool to present engineering system and previous researches have been focusing on the reliability evaluation of multi-state system recently. The Analytical algorithm and Monte Carlo simulation are the major reliability evaluation methods. However, it is inefficient to apply these algorithms to find the optimal multi-state system with greatest reliability in numbers of systems, whose computational time may last for hours. Hence, this paper proposes a new method based on ordinal optimization algorithm and Monte Carlo simulation applied in reliability evaluation. Calculation methods concerning the characteristics of system are defined, which can dramatically and effectively shorten the computational time. An effective and convenient precision and efficiency verification according to the proposed method is illustrated.

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“…If the system in the same sort adds one parallel component, the reliability can refer to equation (2). Then we can get the rough reliability one of all systems--calculation method one.…”

Section: Process Of the MC Modelmentioning

confidence: 99%

“…Previous researches have been focusing on the reliability evaluation of multi-state system recently [2][3][4][5][6]. As time went by, the commonly used evaluation method of multi-state system consists of two algorithms, Analytical algorithm and Monte Carlo simulation [7][8].…”

Section: Introductionmentioning

confidence: 99%

Reliability Evaluation and Selection in Multi-State System

Hu¹,

Liu²,

Hong-jie³

2018

dteees

View full text Add to dashboard Cite

show abstract

“…Then, the pair [ ( ), ( )] Bel X Pl X of functions composes an integrated uncertainty interval of event , which can be used to represent the interval state probability of focal element [11].…”

Section: 2belief Function Theorymentioning

confidence: 99%

“…Instead, belief universal generating function (BUGF) method combined of belief function theory [9] and universal generating function method (UGF) [10] is adopted. The BUGF method [11] can track the correlation of the original data well and keep it to the end of the calculation, and can get narrower and more accurate interval reliability indexes of the power generation system.…”

mentioning

confidence: 99%

Interval Reliability Assessment of Power System under Epistemic Uncertainty Based on Belief UGF Method

Wang

Ding³

et al. 2017

IOP Conf. Ser.: Mater. Sci. Eng.

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“…The UGF method is proposed by Ushakov, and Levitin first uses it to study a multistage expansion problem and a replacement schedule optimization problem for multistate series‐parallel systems. So far, the UGF method has been proven to be an effective method for calculating the reliability of various systems . In addition, using the UGF to calculate the reliability of the clustering, mesh structure, and some similar linear models (LCCS, LMCCS) has been proven to be feasible in sources and .…”

Section: Introductionmentioning

confidence: 99%

Reliability evaluation for wireless sensor networks with chain structures using the universal generating function

Liu

Yin

Yang

et al. 2017

Quality & Reliability Eng

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In different protocols, wireless sensor networks (WSNs) form different topologies. The reliability evaluation of a WSN whose topology is a chain is studied in this paper. A bidirectional data transmission tree (BDTT) model is established to describe the process of data fusion and transmission on a WSN with a chain structure. From the characteristics of the measurement errors, the number of fusions, and measurement credibility, 3 definitions for the reliability of a BDTT are presented. Based on the universal generating function technique, an algorithm is suggested for evaluating the reliability of a BDTT. In the algorithm, a BDTT model is divided into 2 branches, and 2 new composition operators are defined according to data fusion and transmission. We use the first operator to obtain the u‐function of each branch and the second one to combine the u‐functions of 2 branches and obtain the u‐function of the BDTT. The process of calculating the reliability of a BDTT is illustrated with an example, and the effects of measurement errors, the number of fusions, and measurement credibility on the system reliability are analyzed.

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Belief Universal Generating Function Analysis of Multi-State Systems Under Epistemic Uncertainty and Common Cause Failures

Cited by 68 publications

References 37 publications

Reliability Evaluation and Selection in Multi-State System

Reliability Evaluation and Selection in Multi-State System

Interval Reliability Assessment of Power System under Epistemic Uncertainty Based on Belief UGF Method

Reliability evaluation for wireless sensor networks with chain structures using the universal generating function

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