Analysis of UHF signal using prediction model

With increasing interest in the reduction of cost for operation and maintenance of SF₆ gas-insulated switchgear (GIS), various methods of condition monitoring have been developed and used in conjunction with highly sensitive sensors and advanced digital signal processing techniques. Detection of partial-discharge signals in GIS using ultra-high frequency (UHF) technique has gained wide acceptance in research and industry. Unlike approaches of fast Fourier transformation and discrete wavelet transformation (DWT), a novel method of using an adaptive linear combiner as a prediction model to analyze UHF signals is introduced in this paper. Successful results are obtained by applying this new method on field data measured by a UHF coupler. The feasibility of this new approach is studied and proved by the statistical distributions of the trained weights.