Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Nauman Munir"'
Publikováno v:
IEEE Access, Vol 10, Pp 119734-119744 (2022)
Precise knowledge of secondary arc extinction instant and fault nature (temporary or permanent) is necessary for auto-reclosing after a single line-to-ground fault. Existing intelligent reclosing schemes rely on the extraction of appropriate features
Externí odkaz:
https://doaj.org/article/a2c91551508a4a979c285bdf1f4eccb4
Autor:
Jinhyun Park, Seong-Jin Han, Nauman Munir, Yun-Taek Yeom, Sung-Jin Song, Hak-Joon Kim, Se-Gon Kwon
Publikováno v:
Nuclear Engineering and Technology, Vol 51, Iss 7, Pp 1784-1790 (2019)
Accurate and consistent characterization of defects in steam generator tubes (SGT) in nuclear power plants is one of the key issues in the field of nondestructive testing since the large number of signals to be analyzed in a time-limited in-service i
Externí odkaz:
https://doaj.org/article/b5b226b7d5f844cf9d4a0170c1f53dc2
Publikováno v:
Batteries, Vol 8, Iss 3, p 21 (2022)
Lithium-ion batteries, which have high energy density, are the most suitable batteries for use in high-tech electromechanical applications requiring high performance. Because one of the important components that determines the efficiency of lithium-i
Externí odkaz:
https://doaj.org/article/304776fdc0db468e9780f43b0767cd18
Publikováno v:
IEEE Transactions on Power Delivery. 37:4775-4785
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::70b809d8a5beda0c44966671424ec4c0
https://doi.org/10.1109/tpwrd.2022.3159256
https://doi.org/10.1109/tpwrd.2022.3159256
Publikováno v:
Journal of the Korean Physical Society. 75:978-984
The interpretation of Lamb wave signals in real transducers needs careful excitation of Lamb wave mode and complex signal processing technique. In this study, the low mode antisymmetric Lamb wave is generated at one side and recorded at the other sid
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::241a8b8c4edada6c8b3d8f66a8f41550
https://doi.org/10.3938/jkps.75.978
https://doi.org/10.3938/jkps.75.978
Autor:
Se-Gon Kwon, Hak-Joon Kim, Nauman Munir, Jinhyun Park, Yun-Taek Yeom, Sung-Jin Song, Seong-Jin Han
Publikováno v:
Nuclear Engineering and Technology, Vol 51, Iss 7, Pp 1784-1790 (2019)
Accurate and consistent characterization of defects in steam generator tubes (SGT) in nuclear power plants is one of the key issues in the field of nondestructive testing since the large number of signals to be analyzed in a time-limited in-service i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e5c953281ee58b18ac2240fa9cc9d8b2
http://www.sciencedirect.com/science/article/pii/S1738573319302414
http://www.sciencedirect.com/science/article/pii/S1738573319302414
Publikováno v:
Optik. 253:168607
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ae95a0c365ff195de6d6adad41fe908a
https://doi.org/10.1016/j.ijleo.2022.168607
https://doi.org/10.1016/j.ijleo.2022.168607
Publikováno v:
Journal of Mechanical Science and Technology. 32:3073-3080
Ultrasonic signal classification of defects in weldment, in automatic fashion, is an active area of research and many pattern recognition approaches have been developed to classify ultrasonic signals correctly. However, most of the developed algorith
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::39eacce61a5426116c4ef53e6f8b1eea
https://doi.org/10.1007/s12206-018-0610-1
https://doi.org/10.1007/s12206-018-0610-1
Publikováno v:
NDT & E International. 111:102218
The industrial application of deep neural networks to automate the ultrasonic weldment flaw classification system has some limitations. The major problem that affects the classification performance of deep neural networks is the noise in the ultrason
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aeac369642e4f4b116596a0d8439220e
https://doi.org/10.1016/j.ndteint.2020.102218
https://doi.org/10.1016/j.ndteint.2020.102218
Publikováno v:
Ultrasonics. 94
Ultrasonic flaw classification in weldment is an active area of research and many artificial intelligence approaches have been applied to automate this process. However, in the industrial applications, the ultrasonic flaw signals are not noise free a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a6b0fc7833d74b2990236fd8010187d1
https://pubmed.ncbi.nlm.nih.gov/30558810
https://pubmed.ncbi.nlm.nih.gov/30558810