• International Journal of Reliability and Applications
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• v.12 no.2
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• pp.103-116
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• 2011

A series-parallel system with independent but non-identical components is considered. The expressions have been derived for the joint reliability importance (JRI) of m (${\geq}2$) components, chosen from a series-parallel system. JRIs of components of two different series-parallel systems are studied analytically and graphically.

• Proceedings of the KIEE Conference
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• summer
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• pp.806-808
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• 2004

The series and parallel connection is essential for increasing power ratings of resistive type for fault current limiters. To increase voltage class, components are connected in series and to increase current level to the nominal value, they are connected in parallel. There are two ways to connect components in series and parallel. First, connected in series and then the module connects to the parallel. Second, connected in parallel and the module connects to the series. We have studied for the two ways. In this paper, we particularly investigated way to connect components in parallel first This way has the advantage of inducing effective simultaneous quench without any other devices, for example, the thing which is inducing magnetic field to the limiting and shunt resistors. And also we studied for the endurance of component which is patterned to the bi-spiral for prospective fault current. It is very important to understand this, because SFCL will use as the only device to decrease burden of circuit breaker. As experimental results, limiting component patterned to bi-spiral endures fault current up to 30kA and it works well, in parallel to series connection,

• International Journal of Reliability and Applications
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• v.3 no.4
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• pp.173-184
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• 2002

This paper introduces the joint structural importance of two components in a coherent system. Some relationships between joint structural importance and marginal structural importance are presented. It is shown that the sign of Joint structural importance can be determined, in advance, without computation in some special structures. The joint structural importance of two components in some series-parallel and parallel-series systems are established. Some practical examples are presented to elucidate some of the derived results.

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.461-469
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• 2003

In this paper, we consider the series and parallel system which include two components. We assume that the lifetimes of two components follow the bivariate Pareto model with random censored data. We obtain the estimators and approximated confidence intervals of the reliabilities for series and parallel systems based on maximum likelihood estimator and the relative frequency, respectively. Also we present a numerical example by giving a data set which is generated by computer.

• International Journal of Reliability and Applications
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• v.8 no.2
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• pp.137-151
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• 2007

Posbist reliability of typical systems is preliminarily discussed in Cai (1991). In this paper, we focus on the posbist reliability analysis of some typical systems in depth. First, the lifetime of the system is dealt as a fuzzy variable defined on the possibility space (U, ${\phi}$, $P_{oss}$) and the universe of discourse is expanded from (0, $+{\infty}$) to ($-{\infty},\;+{\infty}$). Then, a concrete possibility distribution function of the fuzzy variable is given, i.e., a Gaussian fuzzy variable. Finally, posbist reliability of typical systems (series, parallel, series-parallel, parallel-series, cold redundant system) is deduced. The expansion makes the proofs of some theorems straightforward and allows us to easily obtain the posbist reliability of typical systems. To illustrate the method a numerical example is given.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.6
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• pp.390-395
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• 2005

Sunspots are dark areas that grow and decay on the lowest level of the sun that is visible from the Earth. Shot-term predictions of solar activity are essential to help plan missions and to design satellites that will survive for their useful lifetimes. This paper presents a parallel-structure fuzzy system(PSFS) for prediction of sunspot number time series. The PSFS consists of a multiple number of component fuzzy systems connected in parallel. Each component fuzzy system in the PSFS predicts future data independently based on its past time series data with different embedding dimension and time delay. An embedding dimension determines the number of inputs of each component fuzzy system and a time delay decides the interval of inputs of the time series. According to the embedding dimension and the time delay, the component fuzzy system takes various input-output pairs. The PSFS determines the final predicted value as an average of all the outputs of the component fuzzy systems in order to reduce error accumulation effect.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.233-242
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• 1995

In this paper, we introduce the identification model of dynamic system using the neural networks, We propose two identification models. The output of the parallel identification model is a linear combination of its past values as well as those of the input. The series-parallel model is a linear combination of the past values in the input and output of the plant. To generate stable adaptive laws, we prove that the series-parallel model is found to be proferable.

• International Journal of Reliability and Applications
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• v.9 no.2
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• pp.153-165
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• 2008

This paper discusses the reliability equivalences of a series-parallel system. The system components are assumed to be independent and identical. The failure rates of the system components are functions of time and follow Weibull distribution. Three different methods are used to improve the given system reliability. The reliability equivalence factor is obtained using the reliability function. The fractiles of the original and improved systems are also obtained. Numerical example is presented to interpret how to utilize the obtained results.

• Smart Structures and Systems
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• v.13 no.4
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• pp.711-730
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• 2014

In this paper the system dynamic influences in actuators with variable stiffness as contemporary used in robotics for safety and efficiency reasons are investigated. Therefore, different configurations of serial and parallel elasticities are modeled by dynamic equations and linearized transfer functions. The latter ones are used to identify the characteristic behavior of the different systems and to study the effect of the different elasticities. As such actuation concepts are often used to reach energy-efficient operation, a power consumption analysis of the configurations is performed. From the comparison of this with the system dynamics, strategies to select and control stiffness are derived. Those are based on matching the natural frequencies or antiresonance modes of the actuation system to the frequency of the trajectory. Results show that exclusive serial and parallel elasticity can minimize power consumption when tuning the system to the natural frequencies. Antiresonance modes are an additional possibility for stiffness control in the series elastic setup. Configurations combining both types of elasticities do not provide further advantages regarding power reduction but an input parallel elasticity might enable for more versatile stiffness selection. Yet, design and control effort increase in such solutions. Topologies incorporating output parallel elasticity showed not to be beneficial in the chosen example but might do so in specific applications.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.2
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• pp.113-121
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• 2000

This paper presents a parallel-structure fuzzy system(PSFS) for prediction of time series data. The PSFS consists of a multiple number of fuzzy systems connected in parallel. Each component fuzzy system in the PSFS predicts the same future data independently based on its past time series data with different embedding dimension and time delay. The component fuzzy systems are characterized by multiple-input singleoutput( MIS0) Sugeno-type fuzzy rules modeled by clustering input-output product space data. The optimal embedding dimension for each component fuzzy system is chosen to have superior prediction performance for a given value of time delay. The PSFS determines the final prediction result by averaging the outputs of all the component fuzzy systems excluding the predicted data with the minimum and the maximum values in order to reduce error accumulation effect.