State Evaluation Model of High voltage Switchgear Based on Fuzzy Set-valued Statistical Method and Kernel Vector Space Model

The traditional high voltage switchgear (HVS) state evaluation model mostly adopts electrical test, live detection and historical data, neglecting the influence of real-time operation data HVS composition equipment on results. This paper proposes a based fuzzy set-valued statistics method kernel vector space test on-line monitoring data. First all, according to components switchgear, is described index system established. Secondly, used construct mathematical weight. Then, introduced, Gaussian function map sample features high-dimensional feature space. indicator ideal high-voltage status level standard are defined in space, angle-weighted cosine between two vectors calculated as closeness level, then obtained. Finally, real power supply company western China simulated. results show that greater degree is, closer corresponding normal state, contrary, smaller fault state.