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Journals / Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi / 2008 / Cilt: 23 - Sayı: 3

Design optimization of submersible induction motors by multiobjective fuzzy genetic algorithm

Çok kriterli bulanık genetik algoritma ile dalgıç asenkron motorların tasarım optimizasyonu

Mehmet ÇUNKAŞ
Abdullah ÜRKMEZ
Pages
645–653
Publication Date
2022-10-18
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The optimization results show the effectiveness and achievement of the proposed method.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This paper presents multiobjective fuzzy genetic algorithm optimization approach to a submersible motor design.
📊
Key Findings & Data:Utilizing the concept of fuzzy sets and convex fuzzy decision making, the motor design task is formulated as a multiobjective fuzzy optimization problem and solved using a genetic algorithm.
💡
Conclusion & Impact:The optimization results show the effectiveness and achievement of the proposed method.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

This paper presents multiobjective fuzzy genetic algorithm optimization approach to a submersible motor design. Utilizing the concept of fuzzy sets and convex fuzzy decision making, the motor design task is formulated as a multiobjective fuzzy optimization problem and solved using a genetic algorithm. The two-dimensional Finite Element Method (FEM) is then used to confirm the validity of the optimal design. The optimization results show the effectiveness and achievement of the proposed method.

Özet

Bu çalışmada, dalgıç asenkron motorların tasarım optimizasyonu çok kriterli genetik algoritma kullanılarak gerçekleştirildi. Motor tasarımı, bulanık kümeler ve bulanık karar yapma kavramlarından faydalanarak çok kriterli bulanık optimizasyon problemi olarak formüle edildi ve genetik algoritmalar ile çözüldü. Optimal tasarımın geçerliliğini doğrulamak için iki boyutlu Sonlu Elemanlar Yöntemi (SEY) kullanıldı. Optimizasyon sonuçları amaçlanan yöntemin etkisini ve başarısını gösterdi.

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Cite This Article

ÇUNKAŞ, M., ÜRKMEZ, A. (2022). Design optimization of submersible induction motors by multiobjective fuzzy genetic algorithm. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, Cilt: 23 - Sayı: 3, 645–653. https://ajindex.com/articles/523984

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