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<p>The key objective of the present study is to investigate the impact of intuitionistic and dual hesitant fuzzy numbers on the reliability measures of wind turbines under the concept of various redundancies. Here, three different models of wind turbines are proposed and function derived for all using path tracing method. The reliability behaviour of models analyzed using intuitionistic fuzzy sets, and dual hesitant fuzzy numbers with different membership and non-membership functions. The uncertainty in data is handled using triangular fuzzy numbers and reliability is evaluated using the Weibull distribution. The highest reliability attains at Min R (<InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41870_2025_2796_Article_IEq1.gif" Format="GIF" Height="17" Rendition="HTML" Resolution="72" Type="Linedraw" Width="45" /> </InlineMediaObject> <EquationSource Format="TEX">\(\alpha_{2} ,\,\beta_{2}\)</EquationSource> </InlineEquation>) = (0.999999, 0.999915) for α = 0.6 (β = 0.4) and t = 5 for models 2 and 3. The study concludes that these fuzzy set extensions hold imprecise and uncertain conditions that are difficult to handle in real-life problems by traditional methods. It is observed that the behaviour of models having redundancy component-wise outperforms the complete system redundancy. The results may be utilized by system designers and maintenance engineers.</p>

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Fuzzy reliability analysis of wind turbines using path tracing method and fuzzy set extensions

  • 期刊论文

  • 发表日期：

    2025年10月25日

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  • Kanak Saini,
  • Monika Saini,
  • Ashish Kumar,
  • Dinesh Kumar Saini

摘要

The key objective of the present study is to investigate the impact of intuitionistic and dual hesitant fuzzy numbers on the reliability measures of wind turbines under the concept of various redundancies. Here, three different models of wind turbines are proposed and function derived for all using path tracing method. The reliability behaviour of models analyzed using intuitionistic fuzzy sets, and dual hesitant fuzzy numbers with different membership and non-membership functions. The uncertainty in data is handled using triangular fuzzy numbers and reliability is evaluated using the Weibull distribution. The highest reliability attains at Min R ( \(\alpha_{2} ,\,\beta_{2}\) ) = (0.999999, 0.999915) for α = 0.6 (β = 0.4) and t = 5 for models 2 and 3. The study concludes that these fuzzy set extensions hold imprecise and uncertain conditions that are difficult to handle in real-life problems by traditional methods. It is observed that the behaviour of models having redundancy component-wise outperforms the complete system redundancy. The results may be utilized by system designers and maintenance engineers.