| IEEE Access | |
| Separation Techniques of Partial Discharges and Electrical Noise Sources: A Review of Recent Progress | |
| Firdaus Muhammad-Sukki1  Jorge Alfredo Ardila-Rey1  Matias Patricio Cerda-Luna2  Andre Luiz Andreoli3  Bruno Albuquerque de Castro4  Rodrigo Andres Rozas-Valderrama5  | |
| [1] Departamento de Ingenier&x00ED;a El&x00E9;a, Santiago de Chile, Chile;cnica Federico Santa Mar&x00ED;ctrica, Universidad T&x00E9; | |
| 关键词: Partial discharges; separation techniques; noise sources; progress; review; | |
| DOI : 10.1109/ACCESS.2020.3035249 | |
| 来源: DOAJ | |
【 摘 要 】
Partial discharge (PD) monitoring is one of the most used tools for diagnosing the condition of electrical equipment and machines that operate normally at high voltage levels. Ideally, PD identification can be easily done if there is a single source acting over the electrical asset during the measurement. However, in industrial environments, it is common to find the presence of multiple sources acting simultaneously, which hinders the identification process, due to sources of greater amplitude hiding the presence of other types of sources of lesser amplitude that could eventually be much more harmful to the insulation system. In this sense, the separation of PD through the use of clustering techniques allows individual source recognition once they have been clearly separated. This article describes the main clustering techniques that have been used over time to separate PD sources and electrical noise. The results obtained by the different authors in the utilization of each technique demonstrates good performance in terms of separation.
【 授权许可】
Unknown