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Journal of the Korean Society of Manufacturing Technology Engineers - Vol. 29, No. 2, pp.83-88

ISSN: 2508-5107 (Online)

Print publication date 15 Apr 2020

Received 16 Mar 2020 Revised 26 Mar 2020 Accepted 27 Mar 2020

DOI: https://doi.org/10.7735/ksmte.2020.29.2.83

Random Forest 방법을 적용한 초저유량 하이드로싸이클론 설계 및 성능예측

김창원^a ; 서영진^b^{, *}

Design and Performance Prediction of Ultra-low Flow Hydrocyclone Using the Random Forest Method

Changwon Kim^a ; Youngjin Seo^b^{, *}

aDepartment of Medical Assistant Robot, Korea Institute of Machinery and Materials
bDepartment of Mechanical Engineering, Kumoh National Institute of Technology

Correspondence to: ^*Tel.: +82-54-478-7302 E-mail address: yjseo@kumoh.ac.kr (Youngjin Seo).

Abstract

A hydrocyclone is a particle separation device. Due to their simple shapes and real-time particle separation functions, hydrocyclones are used in several industrial sites. However, the design of a hydrocyclone through numerical analysis takes prolonged time. In this study, a machine learning method is utilized to reduce the hydrocyclone design time. By using a random forest-based learning algorithm, the following three tasks were accomplished: particle separation efficiency was predicted under given design parameters; design parameters were extracted for a given bid size and the corresponding separation efficiency; finally, an extrapolation-based separation efficiency was investigated. The performance of the proposed learning algorithm-based prediction is demonstrated by comparing the results with numerical analysis data.

Keywords:

Hydro cyclone, Numerical analysis, Machine learning, Random forest, Design parameter prediction

Acknowledgments

본 연구는 금오공과대학교 교수연구년제에 의하여 연구된 실적물입니다.

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