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Surrogate-based optimization design and data mining of an axial fan for a refrigerator

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成果类型:
会议论文
作者:
Kuan Tan;Youwei He;Guocheng Wang
作者机构:
[Guocheng Wang] Yijie Machinery Leasing Co., Ltd of Hengyang, Hengyang, China
[Kuan Tan; Youwei He] College of Mechanical Engineering, University of South China, Hengyang, China
语种:
英文
关键词:
the axial fan;surrogate-based optimization;data mining
年:
2024
页码:
1623-1628
会议名称:
2024 3rd International Conference on Energy, Power and Electrical Technology (ICEPET)
会议论文集名称:
2024 3rd International Conference on Energy, Power and Electrical Technology (ICEPET)
会议时间:
17 May 2024
会议地点:
Chengdu, China
出版者:
IEEE
ISBN:
979-8-3503-5266-5
机构署名:
本校为其他机构
院系归属:
机械工程学院
摘要:
The efficiency of the axial fan has a direct impact on the cooling performance of refrigerators, so this paper proposes a design optimization and data mining method based on the surrogate model to improve the efficiency of the axial fan and understand the optimization principle behind it. In this paper, the optimization algorithm based on the Kriging model is applied to optimize the axial fan. The candidate points for each evaluation are set to 5 to improve the optimization efficiency, and the final axial fan efficiency is improved by 2.58%. Then, through data mining technology of the Analysis...

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