Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Dongkoo Shon"'
Autor:
Muhammad Farooq Siddique, Wasim Zaman, Saif Ullah, Muhammad Umar, Faisal Saleem, Dongkoo Shon, Tae Hyun Yoon, Dae-Seung Yoo, Jong-Myon Kim
Publikováno v:
Sensors, Vol 24, Iss 22, p 7303 (2024)
Accurate and reliable bearing-fault diagnosis is important for ensuring the efficiency and safety of industrial machinery. This paper presents a novel method for bearing-fault diagnosis using Mel-transformed scalograms obtained from vibrational signa
Externí odkaz:
https://doaj.org/article/eccdcc837e9b4ea4970f75fc03ba346b
Autor:
Rafia Nishat Toma, Yangde Gao, Farzin Piltan, Kichang Im, Dongkoo Shon, Tae Hyun Yoon, Dae-Seung Yoo, Jong-Myon Kim
Publikováno v:
Sensors, Vol 22, Iss 22, p 8958 (2022)
In the machine learning and data science pipelines, feature extraction is considered the most crucial component according to researchers, where generating a discriminative feature matrix is the utmost challenging task to achieve high classification a
Externí odkaz:
https://doaj.org/article/f6397214a8c64d26941ace9fc25297d4
Autor:
Rafia Nishat Toma, Farzin Piltan, Kichang Im, Dongkoo Shon, Tae Hyun Yoon, Dae-Seung Yoo, Jong-Myon Kim
Publikováno v:
Sensors, Vol 22, Iss 13, p 4881 (2022)
Diagnostics of mechanical problems in manufacturing systems are essential to maintaining safety and minimizing expenditures. In this study, an intelligent fault classification model that combines a signal-to-image encoding technique and a convolution
Externí odkaz:
https://doaj.org/article/8673cf56cfe84132918d0d5ed1afaab6
Autor:
Farzin Piltan, Rafia Nishat Toma, Dongkoo Shon, Kichang Im, Hyun-Kyun Choi, Dae-Seung Yoo, Jong-Myon Kim
Publikováno v:
Sensors, Vol 22, Iss 2, p 539 (2022)
Bearings are nonlinear systems that can be used in several industrial applications. In this study, the combination of a strict-feedback backstepping digital twin and machine learning algorithm was developed for bearing crack type/size diagnosis. Acou
Externí odkaz:
https://doaj.org/article/9c71ad2d88da4d4cbd9b3adf11f63127
Publikováno v:
Applied Sciences, Vol 10, Iss 21, p 7639 (2020)
This paper proposes a classification framework for automatic sleep stage detection in both male and female human subjects by analyzing the electroencephalogram (EEG) data of polysomnography (PSG) recorded for three regions of the human brain, i.e., t
Externí odkaz:
https://doaj.org/article/b56bdf419ca140fcbc22e9159e48e589
Publikováno v:
Symmetry, Vol 10, Iss 12, p 681 (2018)
This paper proposes a numerical analysis method for improving risk assessment of radio frequency (RF) hazards. To compare the results of conventional code analysis, the values required for dipole antenna risk assessment, which is widely used in offsh
Externí odkaz:
https://doaj.org/article/5d1df165d232481f92a80224f3065745
Autor:
Bach Phi Duong, Sheraz Ali Khan, Dongkoo Shon, Kichang Im, Jeongho Park, Dong-Sun Lim, Byungtae Jang, Jong-Myon Kim
Publikováno v:
Sensors, Vol 18, Iss 11, p 3740 (2018)
Estimation of the remaining useful life (RUL) of bearings is important to avoid abrupt shutdowns in rotary machines. An important task in RUL estimation is the construction of a suitable health indicator (HI) to infer the bearing condition. Conventio
Externí odkaz:
https://doaj.org/article/fcb38d1b19014fc5b3d2eca4e49984db
Publikováno v:
2023 25th International Conference on Advanced Communication Technology (ICACT).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e9933c2977c5698ca378ea367444af75
https://doi.org/10.23919/icact56868.2023.10079320
https://doi.org/10.23919/icact56868.2023.10079320
Publikováno v:
Inventive Systems and Control ISBN: 9789811910111
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f0ca45101b843529b45261fc6c8d8020
https://doi.org/10.1007/978-981-19-1012-8_45
https://doi.org/10.1007/978-981-19-1012-8_45
Publikováno v:
Applied Sciences, Vol 10, Iss 7639, p 7639 (2020)
Applied Sciences
Volume 10
Issue 21
Applied Sciences
Volume 10
Issue 21
This paper proposes a classification framework for automatic sleep stage detection in both male and female human subjects by analyzing the electroencephalogram (EEG) data of polysomnography (PSG) recorded for three regions of the human brain, i.e., t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0a95bae75ff63c9fa5923f07dbdf6a19
https://www.mdpi.com/2076-3417/10/21/7639
https://www.mdpi.com/2076-3417/10/21/7639