The effectiveness of different sampling rates in vegetation high-impedance fault classification

This paper investigates the alarming fire igniting scenario of High-Impedance Faults (HIF) resulting from the contact of vegetation with the power lines. Our findings are based on a set of experiments performed on a data set of real staged fault-signals sampled by two distinct channels with different band-pass filters. Representations from these two sampling methods are extracted by different signal processing methods and ranked by their discriminative potential. Experimental results obtained by our proposed methodology show the effectiveness of wideband signals sampled at higher frequencies. Their features result in higher separability potential and are more effective at discriminating fault occurrences than ones from the low-frequency channel. As the approach of employing high-frequency signals in such task may be faced with skepticism, the paper also discusses the possible concerns and feasibility of using higher sampling rate technologies for HIF fault classification.