Dynamic Fuzzy Reliability Analysis of Multistate Systems Based on Universal Generating Function

Gao, Peng; Xie, Liyang; Hu, Wei; Chang, Liu; Feng, Jianghua

doi:10.1155/2018/6524629

Cited by 15 publications

(11 citation statements)

References 18 publications

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“…Step 5: Establish improved FMSS availability index Given a target power demand of 3 1.9, 2.1, 2. ( ) 1 3 0 w    kW, the lower and upper bounds of the improved FMSS availability in the α-cut level set for the community-based smart grid can be obtained using the proposed constrained nonlinear parameter-planning model equations (14) and (15). As observed in this case study, the performances of states 3 and 4 overlap with the target power demand, i.e., ( Table 3 compares the results obtained in this study against those obtained using the method reported in [11].…”

Section: Step 3: Establish Fmsc Fugf and Fmss Ispmentioning

confidence: 99%

“…The effectiveness of their model was verified using a system in its design stage. Gao et al [15] considered the system workload and degradation intensity of components to establish their FMSS reliability model. Considering an MSS with multiple uncertain signals, Dong et al [16] introduced the standard interval fuzzy theory to expand the FUGF applicability.…”

Section: Introductionmentioning

confidence: 99%

“…In summary, the FMSS reliability models reported in [13,15,16,[18][19][20] are based on the approach proposed by Ding et al [10], whereas those presented in [12] and [13] are an application of the approach presented in [11] involving the use of an FMSS reliability index to compensate for the drawbacks of the method presented in [10] that utilizes linear TFN to quantify circumstances with non-probabilistic uncertainties. The approach proposed in [11] considers the αcut value in determining the extent to which the stateperformance membership function meets the mission demand.…”

Section: Introductionmentioning

confidence: 99%

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Improved Availability Index for Repairable Fuzzy Multi-State Systems

2020

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Fuzzy multi-state systems (FMSSs) comprise FMS components (FMSCs) aims at analyzing non-probabilistic uncertain circumstances defined by fuzzy state-transition rate and performance numbers. The triangular fuzzy number that features intuitive and algebraic operations is widely used for quantifying fuzziness. This study aims to overcome the drawbacks of the existing FMSS availability index that either does not conform to a normal convex set or is inconsistent with the crisp-circumstance multi-state system (MSS) availability beyond summation over state probabilities that do no equal unity. The proposed method first evaluates the instantaneous state probability (ISP) of FMSCs by establishing the FMSCs Markov model. Subsequently, the FMSSs ISP is evaluated by integrating the FMSCs ISP using the fuzzy universal generating function based on the system-structure function. A "constrained nonlinear parameter programming model" has been developed to evaluate the improved FMSSs availability. The corresponding availability index features the normal convex set whilst fulfilling the MSS theory, which requires state probabilities to equal unity during availability evaluation. The effectiveness of the proposed approach has been verified using an illustrated community-based smart-grid system comprising three FMSCs-solar-and wind-energy systems as well as diesel-generator equipment. Moreover, the results of an independent sensitive analysis provide further insights into the improved FMSSs availability with regard to the time and circumstance fuzziness.

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Section: Step 3: Establish Fmsc Fugf and Fmss Ispmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Improved Availability Index for Repairable Fuzzy Multi-State Systems

2020

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“…The traditional UGF method, however, only solves scenarios where the state performance of a component as well as the corresponding probability are real values and the relationships between components are dependent. To calculate the reliability of the system with fuzzy values, the fuzzy UGF method is presented to extend the traditional UGF with crisp sets 15,16 . Based on the fuzzy UGF method, Dong et al 17 analyze a generalized standard uncertain number to uniformly represent multisource heterogeneous uncertain data and Qiu et al 18 evaluate the fuzzy reliability of series systems with performance sharing between adjacent units.…”

Section: Introductionmentioning

confidence: 99%

Reliability Analysis of Complex Multi-State System Based on Universal Generating Function and Bayesian Network

Liu¹,

Wen²,

Zheng³

et al. 2022

Preprint

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In the complex multi-state system (MSS), reliability analysis is a significant research content, both for equipment design, manufacturing, usage and maintenance. Universal Generating Function (UGF) is an important method in the reliability analysis, which efficiently obtains the system reliability by a fast algebraic procedure. However, when structural relationships between subsystems or components are not clear or without explicit expressions, the UGF method is difficult to use or not applicable at all. Bayesian Network (BN) has a natural advantage in terms of uncertainty inference for the relationship without explicit expressions. For the number of components is extremely large, though, it has the defects of low efficiency. To overcome the respective defects of UGF and BN, a novel reliability analysis method called UGF-BN is proposed for the complex MSS. In the UGF-BN framework, the UGF method is firstly used to analyze the bottom components with a large number. Then probability distributions obtained are taken as the input of BN. Finally, the reliability of the complex MSS is modeled by the BN method. This proposed method improves the computational efficiency, especially for the MSS with the large number of bottom components. Besides, the aircraft reliability-based design optimization based on the UGF-BN method is further studied with budget constraints on mass, power, and cost. Finally, two cases are used to demonstrate and verify the proposed method.

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“…27 Based on the assumptions that the applied loads used in the model were static and the hazard rates of mechanical systems were treated as the constants, Czarnecki, 28 Rackwitz, 29 Torres, 30 et al carried out the studies around the timevariant models for reliability analysis of various kinds of mechanical systems. To fully consider the dependence of hazard rates on strengths of components and applied loads, Wang, 31 Gao, 32 Castaldo, 33 Xie, 34 et al proposed various kinds of dynamic reliability models for mechanical systems by using probability differential equation and order statistics.…”

Section: Introductionmentioning

confidence: 99%

An improved dynamic load-strength interference model for the reliability analysis of aero-engine rotor blade system

Zhao

Ren

Bai

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part G:

Self Cite

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As the power source of an aircraft, aero-engine tends to meet many rigorous requirements for high thrust-weight ratio and reliability with the continuous improvement of aero-engine performance. In this paper, based on the order statistics and stochastic process theory, an improved dynamic load-strength interference (LSI) model was proposed for the reliability analysis of aero-engine rotor blade system, with strength degradation and catastrophic failure involved. In presented model, the “unconventional active” characteristic of rotor blade system, changeable functioning relationships and system-component configurations, was fully considered, which is necessary for both theoretical analysis and engineering application. In addition, to reduce the computation cost, a simplified form of the improved LSI model was also built for convenience of engineering application. To verify the effectiveness of the improved model, reliability of turbojet 7 engine rotor blade system was calculated by the improved LSI model based on the results of static finite element analysis. Compared with the traditional LSI model, the result showed that there were significant differences between the calculation results of the two models, in which the improved model was more appropriate to the practical condition.

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Dynamic Fuzzy Reliability Analysis of Multistate Systems Based on Universal Generating Function

Cited by 15 publications

References 18 publications

Improved Availability Index for Repairable Fuzzy Multi-State Systems

Improved Availability Index for Repairable Fuzzy Multi-State Systems

Reliability Analysis of Complex Multi-State System Based on Universal Generating Function and Bayesian Network

An improved dynamic load-strength interference model for the reliability analysis of aero-engine rotor blade system

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