SUBSPECIES ANALYSIS OF PARTIAL DISCHARGE DATA FROM A GENERATOR STATORCONDUCTOR

Partial discharge (PD) pattern recognition systems are often based on analysis of the data structure as a whole. This approach may not expla in the underlying discharge processes. An alternative concept is propo sed which is based on the examination and analysis of the subspecies i dentifiable in the data. PD data obtained from a generator stator cond uctor are used to demonstrate this approach. Using well-behaved data i t is possible to identify two distinctive types of discharges originat ing from a generator stator conductor. One type has properties ascriba ble to surface discharges, whereas the other type exhibits properties akin to those from internal discharges. The approach allows ill-behave d PD data to be segmented in a supervised manner using knowledge about the likely behaviour of different types of PD. This permits individua l PD generating mechanisms to be monitored, which may be difficult to achieve through analysis of the overall magnitude and phase distributi ons. Using the method, it is demonstrated that the surface discharges have a magnitude distribution whose shape is influenced by a multivalu ed relationship with the phase distribution. These relationships are o bscured if magnitude distribution only is used for the analysis but ar e observable using subspecies analysis.