In order to reduce the occurrence of partial discharge recognition misjudgment and improve the accuracy of pattern recognition of GIS equipment

we discussed the resemblance of different partial discharges. Adopted two common classifiers to diagnose typical faults by the hierarchical identification method

generalized the types of partial discharge of GIS existing in the misjudgment phenomenon

and analyzed the resemblanc of the types of partial discharge. Moreover

we summarized the causes of misjudgment

for example

the instability of free metal particles is the causes of misjudgment

and the position of the sensor distance from the discharge source determines whether the misjudgment of the floating discharge can occur. At the same time

we studied the rationality of the traditional partial discharge type division of GIS. Finally

the accuracy of pattern recognition of the two classifiers was compared by the recognition rate and decision reliability. The research shows that the recognition confidence of protrusion discharge is highest

the identification rate of air bubbles in insulator discharge is highest

and the recognition effect of SVM is better than BP neural network. The research results lay a foundation for the high efficiency of the follow-up work

such as

partial discharge pattern recognition

risk assessment of partial discharge

etc.