Importance analysis in two kinds of redundant systems: k-out-of-n and consecutive k-out-of-n: F systems

The voting system is a kind of redundant system, and the k-out-of- n system and consecutive k-out-of- n system have been widely used in engineering practice. In this article, the marginal reliability importance and joint reliability importance in k-out-of- n: F systems and consecutive k-out-of- n: F systems are studied for some situations. Then, some properties and relevant remarks of the marginal reliability importance and joint reliability importance in two kinds of system models are analyzed for parameters p, k, and n. Finally, an oil pump transportation system is used to demonstrate the proposed method and illustrate the feasibility and practicality of the model.

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New Voters for Redundant Systems

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.3426869 ◽

1975 ◽

Vol 97 (1) ◽

pp. 41-45 ◽

Cited By ~ 25

Author(s):

R. B. Broen

Keyword(s):

Smooth Function ◽

Output Signal ◽

Weighted Average ◽

Direct Calculation ◽

Fault Isolation ◽

Function Approach ◽

Redundant System ◽

Isolation System ◽

Input Signals ◽

Redundant Systems

This paper describes a class of redundant voters which compute and provide a “correct” output signal given a set of redundant input signals. The output is determined as a continuous smooth function of the redundant inputs using a weighted “average.” This type of voter tends to minimize switching transients since the isolation of faulty signals is achieved through a continuous numerical weighting. Equalization schemes which are normally required in voter designs to inhibit adverse transients during a channel failure are negated by this method. This function approach to designing a voter and fault isolation system provides for direct calculation of the characteristics of the output signal, given known characteristics of the inputs. Using this proposed method, a voter can be designed to provide a weighted average of the remaining good signals of a redundant system in the presence of one or more failed signal channels. Computed examples of voter output for assumed values of voter input signals are given for one representative candidate voter when used in configurations for both triply redundant and quadruply redundant systems.

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ON CONDITIONAL MARGINAL AND CONDITIONAL JOINT RELIABILITY IMPORTANCE

International Journal of Reliability Quality and Safety Engineering ◽

10.1142/s0218539311004032 ◽

2011 ◽

Vol 18 (02) ◽

pp. 119-138 ◽

Cited By ~ 13

Author(s):

MONIKA RANI ◽

KANCHAN JAIN ◽

ISHA DEWAN

Keyword(s):

Electronic System ◽

Reliability Function ◽

Bridge Structure ◽

Coherent Systems ◽

Joint Reliability ◽

Two Systems ◽

The Difference ◽

Schur Convexity ◽

Marginal Reliability ◽

Three Components

The reliability importance of one or more components when another component is assumed to be working/non-working is measured by Conditional Marginal Reliability Importance (CMRI) and Conditional Joint Reliability Importance (CJRI) respectively. We consider two systems viz the series-in-parallel and series-parallel. The expressions for CMRI and CJRI are derived for both the systems when the components are independent but not identically distributed. It is shown that the sign of the joint importance of three components and Conditional Joint Importance (CJI) can be determined using Schur-convexity (concavity) of the reliability function. The difference in the reliability functions of two coherent systems with n ≥ 3 statistically independent and with dependent components is derived. It is shown to be measured by their covariance, the JRI and the CJRIs. CMRIs and CJRIs of a phased type electronic system and a bridge structure are worked out.

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Reliability and Importance Measures for Combined m-Consecutive-k-Out-of-n: F and Consecutive-kb-Out-of-n: F Systems with Non-Homogeneous Markov-Dependent Components

International Journal of Reliability Quality and Safety Engineering ◽

10.1142/s0218539318500225 ◽

2018 ◽

Vol 25 (05) ◽

pp. 1850022 ◽

Cited By ~ 2

Author(s):

Mahmoud Boushaba ◽

Azzedine Benyahia

Keyword(s):

Closed Form ◽

Generating Function ◽

System Reliability ◽

Probability Generating Function ◽

Importance Measure ◽

Joint Reliability ◽

Independent Case ◽

New Formula ◽

Marginal Reliability ◽

F System

A Combined [Formula: see text]-Consecutive-[Formula: see text]-out-of-[Formula: see text] and Consecutive-[Formula: see text]-out-of-[Formula: see text]: F System consists of [Formula: see text] components ordered in a line such that the system fails iff there exist at least [Formula: see text] consecutive failed components, or at least [Formula: see text] nonoverlapping runs of [Formula: see text] consecutive failed components, where [Formula: see text]. This system was been introduced by Mohan et al. [P. Mohan, M. Agrawal and K. Sen, Combined [Formula: see text]-consecutive-[Formula: see text]-out-of-[Formula: see text]: F and consecutive-[Formula: see text]-out-of-[Formula: see text]: F systems, IEEE Trans. Reliab. 58 (2009) 328–337] where they propose an algorithm to evaluate system reliability by using the (GERT) technique, in the independent case. In this paper, we propose a new formula of the reliability of this system for nonhomogeneous Markov-dependent components. For a Combined [Formula: see text]-Consecutive-[Formula: see text]-out-of-[Formula: see text] and Consecutive-[Formula: see text]-out-of-[Formula: see text]: F System with nonhomogeneous Markov-dependent components, we derive closed-form formulas for the marginal reliability importance measure of a single component, and the joint reliability importance measure of two or more than two components using probability generating function (pgf) and conditional pgf methods.

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A linear m-consecutive-k-out-of-n system with sparse d of non-homogeneous Markov-dependent components

Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability ◽

10.1177/1748006x18776189 ◽

2018 ◽

Vol 233 (3) ◽

pp. 328-337 ◽

Cited By ~ 2

Author(s):

Xiaoyan Zhu ◽

Mahmoud Boushaba ◽

Abdelmoumene Boulahia ◽

Xian Zhao

Keyword(s):

Closed Form ◽

Conditional Probability ◽

Generating Function ◽

System Reliability ◽

Function Method ◽

Probability Generating Function ◽

Importance Measure ◽

Numerical Examples ◽

Joint Reliability ◽

Marginal Reliability

Consider non-homogeneous Markov-dependent components in an m-consecutive- k-out-of- n:F (G) system with sparse [Formula: see text], which consists of [Formula: see text] linearly ordered components. Two failed components are consecutive with sparse [Formula: see text] if and if there are at most [Formula: see text] working components between the two failed components, and the m-consecutive- k-out-of- n:F system with sparse [Formula: see text] fails if and if there exist at least [Formula: see text] non-overlapping runs of [Formula: see text] consecutive failed components with sparse [Formula: see text] for [Formula: see text]. We use conditional probability generating function method to derive uniform closed-form formulas for system reliability, marginal reliability importance measure, and joint reliability importance measure for such the F system and the corresponding G system. We present numerical examples to demonstrate the use of the formulas. Along with the work in this article, we summarize the work on consecutive- k systems of Markov-dependent components in terms of system reliability, marginal reliability importance, and joint reliability importance.

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Developing Static and Dynamic Multimodal Transportation System Models to Estimate Individual Commuter Footprints Using ArcGIS, Google Maps, and Here 360

International Conference on Transportation and Development 2018 ◽

10.1061/9780784481561.024 ◽

2018 ◽

Author(s):

Annemarie Schwanz ◽

Aly M. Tawfik ◽

Moatassem Abdallah ◽

Caroline M. Clevenger

Keyword(s):

Transportation System ◽

Google Maps ◽

Multimodal Transportation ◽

System Models

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Analysis of oil pump vibration in long distance oil transportation system

Journal of Physics Conference Series ◽

10.1088/1742-6596/1681/1/012022 ◽

2020 ◽

Vol 1681 ◽

pp. 012022

Author(s):

Wubin Lin ◽

Baohu Shi ◽

Weiming Li ◽

Zhihai Li ◽

Wei Yu

Keyword(s):

Transportation System ◽

Long Distance ◽

Oil Transportation ◽

Oil Pump

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Reliability Analysis and Imprecise Component Importance Measure of Redundant Systems of OWTs Based on Component Swapping

Applied Sciences ◽

10.3390/app10041432 ◽

2020 ◽

Vol 10 (4) ◽

pp. 1432

Author(s):

Yao Li ◽

Caichao Zhu ◽

Zi Wang

Keyword(s):

Reliability Analysis ◽

Wind Turbines ◽

Offshore Wind ◽

Importance Measure ◽

Offshore Wind Turbine ◽

Component Reliability ◽

Joint Reliability ◽

Component Importance ◽

Attractive Option ◽

Redundant Systems

Due to the high cost of failures of wind turbines, redundancy designs are commonly applied in wind turbines for improving the reliability and availability of systems. For this reason, replacing failed components with other working components of the same type in redundant systems is becoming an attractive option of maintenance strategies towards more resilient systems. To quantitatively evaluate system’s reliability, this paper focuses on the reliability analysis of redundant systems of offshore wind turbines based on swapping existing components. The survival signature-based component swapping method is introduced to describe the new structure-function of the system upon swapping. Furthermore, the reliability model of redundant systems is established using the fault tree and survival signature. Following this, the influences of component swapping on component reliability importance measure (marginal reliability importance and joint reliability importance) without and with considerations of the imprecision of failure rates are explored. Finally, a 5MW offshore wind turbine is presented to show the applicability of the proposed approach for redundant systems, and the results show that the proposed approach can obtain realistic reliability assessment of redundant systems and considering component swapping can significantly improve system reliability.

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Control and Optimization of Air Traffic Networks

Annual Review of Control Robotics and Autonomous Systems ◽

10.1146/annurev-control-070720-080844 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Karthik Gopalakrishnan ◽

Hamsa Balakrishnan

Keyword(s):

Control Strategies ◽

Air Transportation ◽

Transportation System ◽

Air Traffic ◽

Annual Review ◽

Publication Date ◽

Traffic Networks ◽

Markov Jump ◽

Traffic Demand ◽

System Models

The air transportation system connects the world through the transport of goods and people. However, operational inefficiencies such as flight delays and cancellations are prevalent, resulting in economic and environmental impacts. In the first part of this article, we review recent advances in using network analysis techniques to model the interdependencies observed in the air transportation system and to understand the role of airports in connecting populations, serving air traffic demand, and spreading delays. In the second part, we present some of our recent work on using operational data to build dynamical system models of air traffic delay networks. We show that Markov jump linear system models capture many of the salient characteristics of these networked systems. We illustrate how these models can be validated and then used to analyze system properties such as stability and to design optimal control strategies that limit the propagation of disruptions in air traffic networks. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 4 is May 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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