Zobrazeno 1 - 10
of 344
pro vyhledávání: '"Yong Hwa, Kim"'
Publikováno v:
IEEE Access, Vol 12, Pp 115171-115181 (2024)
Effective monitoring and diagnosis of partial discharge (PD) in power equipment are crucial for maintenance, particularly given the expectations of significant increases in energy generation and consumption. Although deep neural networks have been wi
Externí odkaz:
https://doaj.org/article/bb70c4e6114740849986c5ca9cc7fe46
Publikováno v:
IEEE Access, Vol 12, Pp 34993-35007 (2024)
Recently, deep neural networks have shown remarkable success in fault diagnosis in power systems using partial discharges (PDs), thereby enhancing grid asset safety and reliability. However, the prevailing approaches often adopt centralized large-sca
Externí odkaz:
https://doaj.org/article/0190bc07bc454665a9862d9a27d22c98
Publikováno v:
Energies, Vol 17, Iss 15, p 3745 (2024)
Digital substations have adopted a high amount of information and communication technology (ICT) and cyber–physical systems (CPSs) for monitoring and control. As a result, cyber attacks on substations have been increasing and have become a major co
Externí odkaz:
https://doaj.org/article/6d772880291348e0b7ee6f817f495cb0
Publikováno v:
Applied Sciences, Vol 14, Iss 11, p 4498 (2024)
In this paper, we investigate a novel power beacon (PB)-aided wireless sensor-powered non-orthogonal multiple-access (NOMA) Internet-of-Things (IoT) network under imperfect channel state information (CSI). Furthermore, the exact expression outage pro
Externí odkaz:
https://doaj.org/article/70f63146534141dc86998ae73847b2a4
Publikováno v:
IEEE Access, Vol 11, Pp 49378-49392 (2023)
Nowadays, modern technologies in power systems have been attracting more attention, and households can supply a portion of or all of their electricity based on on-site generation at their location. This can be challenging for utilities in terms of mo
Externí odkaz:
https://doaj.org/article/c5fac9bffd04448e89e37f0426a838f3
Publikováno v:
IEEE Access, Vol 11, Pp 37131-37148 (2023)
Machine learning and deep learning techniques are widely used to evaluate intrusion detection systems (IDS) capable of rapidly and automatically recognizing and classifying cyber-attacks on networks and hosts. However, when destructive attacks are be
Externí odkaz:
https://doaj.org/article/cd07f707de5f46acb57a13aa55ba0e10
Publikováno v:
IET Radar, Sonar & Navigation, Vol 16, Iss 5, Pp 825-836 (2022)
Abstract Concentration of drivers on traffic is a vital safety issue; thus, monitoring a driver being on road becomes an essential requirement. The key purpose of supervision is to detect abnormal behaviours of the driver and promptly send warnings t
Externí odkaz:
https://doaj.org/article/9c6bc82ece87469bb242af4cb1ce2012
Autor:
Nhat-Quang Dang, Trong-Tai Ho, Tuyet-Doan Vo-Nguyen, Young-Woo Youn, Hyeon-Soo Choi, Yong-Hwa Kim
Publikováno v:
Energies, Vol 17, Iss 1, p 4 (2023)
Supervised contrastive learning (SCL) has recently emerged as an alternative to conventional machine learning and deep neural networks. In this study, we propose an SCL model with data augmentation techniques using phase-resolved partial discharge (P
Externí odkaz:
https://doaj.org/article/5a26e9dda7da48f2937404fdabff4c2c
Publikováno v:
IEEE Access, Vol 10, Pp 95125-95131 (2022)
One of the most crucial parameters in operating a vacuum interrupter (VI) is internal pressure. The failure of switching or insulation occurs when the pressure rises above a specific level. Characteristics of partial discharge (PD) in VI can be used
Externí odkaz:
https://doaj.org/article/12b35cdde863472cac5957ce0b8fc69c
Publikováno v:
Nuclear Engineering and Technology, Vol 53, Iss 10, Pp 3314-3318 (2021)
This paper presents a mode-matching analysis of the electromagnetic coupling between open cable trays in an indoor structure when an electric-line current is generated as an electromagnetic source. We validated the mode-matching method by comparing t
Externí odkaz:
https://doaj.org/article/5ebe2f04422d45048811783b3153afb0