Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Wongon Kim"'
Autor:
Sunuwe Kim, Soo-Ho Jo, Wongon Kim, Jongmin Park, Jingyo Jeong, Yeongmin Han, Daeil Kim, Byeng Dong Youn
Publikováno v:
IEEE Access, Vol 8, Pp 178295-178310 (2020)
This paper proposes a semi-supervised autoencoder with an auxiliary task (SAAT) to extract a health feature space for power transformer fault diagnosis using dissolved gas analysis (DGA). The health feature space generated by a semi-supervised autoen
Externí odkaz:
https://doaj.org/article/30784f3cb1d24044b0f85653082d18ac
Publikováno v:
Structural and Multidisciplinary Optimization. 66
Autor:
Daeil Kim, Sunuwe Kim, Wongon Kim, Yeongmin Han, Byeng D. Youn, Soo-Ho Jo, Jongmin Park, Jingyo Jeong
Publikováno v:
IEEE Access, Vol 8, Pp 178295-178310 (2020)
This paper proposes a semi-supervised autoencoder with an auxiliary task (SAAT) to extract a health feature space for power transformer fault diagnosis using dissolved gas analysis (DGA). The health feature space generated by a semi-supervised autoen
Publikováno v:
Structural and Multidisciplinary Optimization. 65
Publikováno v:
Mechanical Systems and Signal Processing. 181:109471
Publikováno v:
Reliability Engineering & System Safety. 226:108721
Publikováno v:
Structural and Multidisciplinary Optimization. 60:1619-1644
Computer-aided engineering (CAE) is now an essential instrument that aids in engineering decision-making. Statistical model calibration and validation has recently drawn great attention in the engineering community for its applications in practical C
Autor:
Wongon Kim
Publikováno v:
Theology of Mission. 54:42-72
Publikováno v:
International Journal of Electrical Power & Energy Systems. 136:107619
This paper proposes a new framework, named BDD, which bridges Duval’s method with a deep neural network (DNN) approach for power transformer fault diagnosis using dissolved gas analysis (DGA). The proposed BDD consists of the following three key po