Výsledky vyhledávání - "Byeong-keun Choi"

Akademický článek

A Study on Machine Learning-Based Feature Classification for the Early Diagnosis of Blade Rubbing

Publikováno v: Sensors, Vol 24, Iss 18, p 6013 (2024)

This research focuses on the development of a machine learning-based approach for the early diagnosis of blade rubbing in rotary machinery. In this paper, machine learning-based diagnostic methods are used for blade rubbing early diagnosis, and the f

Externí odkaz: https://doaj.org/article/1f6a5518f48d40e789ce00e8ec8e8183

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Akademický článek

Distance and Density Similarity Based Enhanced k-NN Classifier for Improving Fault Diagnosis Performance of Bearings

Autor: Sharif Uddin, Md. Rashedul Islam, Sheraz Ali Khan, Jaeyoung Kim, Jong-Myon Kim, Seok-Man Sohn, Byeong-Keun Choi

Publikováno v: Shock and Vibration, Vol 2016 (2016)

An enhanced k-nearest neighbor (k-NN) classification algorithm is presented, which uses a density based similarity measure in addition to a distance based similarity measure to improve the diagnostic performance in bearing fault diagnosis. Due to its

Externí odkaz: https://doaj.org/article/75bb876f594b4cb2b1bf28cef25bc5cd

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Akademický článek

Enhanced DET-Based Fault Signature Analysis for Reliable Diagnosis of Single and Multiple-Combined Bearing Defects

Autor: In-Kyu Jeong, Myeongsu Kang, Jaeyoung Kim, Jong-Myon Kim, Jeong-Min Ha, Byeong-Keun Choi

Publikováno v: Shock and Vibration, Vol 2015 (2015)

To early identify cylindrical roller bearing failures, this paper proposes a comprehensive bearing fault diagnosis method, which consists of spectral kurtosis analysis for finding the most informative subband signal well representing abnormal symptom

Externí odkaz: https://doaj.org/article/9985a63965674b5da0182e4dee29f9d0

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Akademický článek

Structural and Electrochemical Properties of Lithium Nickel Oxide Thin Films

Autor: Gyu-bong Cho, Tae-hoon Kwon, Tae-hyun Nam, Sun-chul Huh, Byeong-keun Choi, Hyo-min Jeong, Jung-pil Noh

Publikováno v: Journal of Chemistry, Vol 2014 (2014)

LiNiO2 thin films were fabricated by RF magnetron sputtering. The microstructure of the films was determined by X-ray diffraction and field-emission scanning electron microscopy. The electrochemical properties were investigated with a battery cycler

Externí odkaz: https://doaj.org/article/05e164c720e649388167df2aed577720

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Akademický článek

Confirmation of Thermal Images and Vibration Signals for Intelligent Machine Fault Diagnostics

Autor: Achmad Widodo, Djoeli Satrijo, Toni Prahasto, Gang-Min Lim, Byeong-Keun Choi

Publikováno v: International Journal of Rotating Machinery, Vol 2012 (2012)

This paper deals with the maintenance technique for industrial machinery using the artificial neural network so-called self-organizing map (SOM). The aim of this work is to develop intelligent maintenance system for machinery based on an alternative

Externí odkaz: https://doaj.org/article/39b45f7dc8244765912f495dadbd9382

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