Discussion on classification of impulsive EM noises emitted from power apparatus

Abstract

This paper proposes an automatic classification system for impulsive electromagnetic (EM) noises. The classification is based on the frequency spectrum of EM waves emitted from partial discharges in power apparatus. This concept is validated by confirming the reproducibility of waveforms of EM waves. In order to clarify the effectiveness of our proposal, six defects are considered: a needleplane electrode, a strain insulator, a pin-type insulator, FDF (Forced Draft Fan), CBP (Condensate Booster Pump), and COOL-P (Cooling Water Pump). Neural networks are used to classify the frequency spectrum of EM waves. As a main result, these sources are well classified with a recognition rate of 80% or better. This is supported by treating 1000 EM pulses.