Zobrazeno 1 - 10
of 279
pro vyhledávání: '"series arc fault"'
Autor:
Bin Li, Jinglong Wu
Publikováno v:
IEEE Access, Vol 12, Pp 15410-15418 (2024)
The current of the residential series arc fault is affected by the load type, and the fault feature change is not obvious and contains noise. Therefore, the extraction of fault features will affect the arc fault detection results. To solve this probl
Externí odkaz:
https://doaj.org/article/b08a36cb9854434ab34819b9aa9c9096
Publikováno v:
IEEE Access, Vol 12, Pp 5851-5863 (2024)
The fast and accurate series arc fault (SAF) identification method and its hardware implementation are the key to the development of arc fault circuit interrupter (AFCI) or arc fault detection device (AFDD). The SAF experiments under household multi-
Externí odkaz:
https://doaj.org/article/4d3be360dbc147809a98c73a902a5e6f
Publikováno v:
IEEE Access, Vol 12, Pp 1483-1496 (2024)
The similarity between arc fault current waveforms and nonlinear load currents can lead to misjudgments in arc fault identification methods that rely on arc current. In response to this issue, this paper establishes a unified fault criterion based on
Externí odkaz:
https://doaj.org/article/9fc62f0d362643c980405279af5c3e09
Publikováno v:
Energies, Vol 17, Iss 18, p 4675 (2024)
Aiming at the problem of accurate AC series arc fault detection, this paper proposes a low voltage AC series arc fault intelligent detection model based on deep learning. According to the GB/T 31143—2014 standard, an experimental platform was estab
Externí odkaz:
https://doaj.org/article/dcde959dd54547c6b39cd22492ba9e18
Publikováno v:
Frontiers in Energy Research, Vol 12 (2024)
Given the problem that the existing series arc fault identification methods use existing features such as the time-frequency domain of the current signal as the basis for identification, resulting in relatively limited arc detection solutions, and th
Externí odkaz:
https://doaj.org/article/b62d77040d8d416fbdd0b5921913d273
Autor:
Alaa Hamza Omran, Dalila Mat Said, Siti Maherah Hussin, Sadiq H. Abdulhussein, Nasarudin Ahmad, Haidar Samet
Publikováno v:
Iraqi Journal for Computer Science and Mathematics, Vol 4, Iss 3 (2023)
A DC series arc fault is one of the significant sources of electrical wiring fires in residential buildings. The production of extremely high temperatures may lead to the ignition of nearby combustible materials. The applications of arc fault diagnos
Externí odkaz:
https://doaj.org/article/4af8bd1eb87f47b6aae40ccec54f17e0
Publikováno v:
Energies, Vol 17, Iss 6, p 1412 (2024)
Arc faults are the main cause of electrical fires according to national fire data statistics. Intensive studies of artificial intelligence-based arc fault detection methods have been carried out and achieved a high detection accuracy. However, the co
Externí odkaz:
https://doaj.org/article/f61944ec8c0b43a69a16156cffe012b9
Publikováno v:
Sensors, Vol 24, Iss 3, p 959 (2024)
Under the conditions of a mechanical fault in a motor, mechanical vibration of a specific frequency can be generated. The electrical contact points directly connected to the motor can vibrate at the same frequency. The electrical contact points with
Externí odkaz:
https://doaj.org/article/32e3fc9534db4290b479f67a9c676c59
Publikováno v:
International Journal of Metrology and Quality Engineering, Vol 15, p 3 (2024)
The detection of multi-feature fusion is a crucial approach to address the issue of series arc fault detection. Effective feature selection plays a vital role in enhancing the accuracy of the classifier and reducing system complexity. In this study,
Externí odkaz:
https://doaj.org/article/00fc7f9065f64c8bb88ac006b52616d3
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.