Separation techniques of partial discharges and electrical noise sources: A review of recent progress

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.