Fuzzy reliability evaluation of linear &lt;i&gt;m&lt;/i&gt;-consecutive weighted-&lt;i&gt;k&lt;/i&gt;-out-of-&lt;i&gt;r&lt;/i&gt;-from-&lt;i&gt;n&lt;/i&gt;: F systems

Negi, Seema; Singh, Sukhwinder

doi:10.1504/ijcsm.2019.10025671

IJCSM

2019

DOI: 10.1504/ijcsm.2019.10025671

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Fuzzy reliability evaluation of linear m-consecutive weighted-k-out-of-r-from-n: F systems

Seema Negi

Sukhwinder Singh

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Reliability assessment of wind turbine generators by fuzzy universal generating function

Huang¹,

Xiahou²,

Li³

et al. 2021

Eksploatacja i Niezawodność – Maintenance and Reliability

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Wind power has been widely used in the past decade because of its safety and cleanness. Double fed induction generator (DFIG), as one of the most popular wind turbine generators, suffers from degradation. Therefore, reliability assessment for this type of generator is of great significance. The DFIG can be characterized as a multi-state system (MSS) whose components have more than two states. However, due to the limited data and/or vague judgments from experts, it is difficult to obtain the accurate values of the states and thus it inevitably contains epistemic uncertainty. In this paper, the fuzzy universal generating function (FUGF) method is utilized to conduct the reliability assessment of the DFIG by describing the states using fuzzy numbers. First, the fuzzy states of the DFIG system’s components are defined and the entire system state is calculated based the system structure function. Second, all components’ states are determined as triangular fuzzy numbers (TFN) according to experts’ experiences. Finally, the reliability assessment of the DFIG based on the FUGF is conducted.

show abstract

Reliability assessment of wind turbine generators by fuzzy universal generating function

Huang¹,

Xiahou²,

Li³

et al. 2021

Eksploatacja i Niezawodność – Maintenance and Reliability

View full text Add to dashboard Cite

show abstract

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Fuzzy reliability evaluation of linear <i>m</i>-consecutive weighted-<i>k</i>-out-of-<i>r</i>-from-<i>n</i>: F systems

Cited by 1 publication

References 0 publications

Reliability assessment of wind turbine generators by fuzzy universal generating function

Reliability assessment of wind turbine generators by fuzzy universal generating function

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