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Journal : Indonesian Journal of Electrical Engineering and Computer Science

A leakage current estimation based on thermal image of polymer insulator Darwison Darwison; Syukri Arief; Hairul Abral; Ariadi Hazmi; M. H. Ahmad; Eka Putra Waldi; Rudy Fernandez
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 3: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i3.pp1096-1106

Abstract

Polymer insulators tend to fail because of the climatic and environmental conditions. The failure occurs when the surface of insulator is contaminated by sea salt or cement dust which lead to partial discharge (PD). Leakage currents will increase by PD that causes deterioration of insulation. To predict the insulation failures, an  adaptive neurofuzzy inference system (ANFIS) method using initial color detection processes are proposed to estimate the leakage currents based on the polymer insulator thermal images (infrared signature). In this study, the sodium chloride and kaolin are used as pollutants of the polymer insulator according to IEC 60507 standards. Then, the insulator is tested in the laboratory using AC high voltage applied at 18 kV where the temperature detection is controlled at 26° C and 70% RH (relative humidity). The percentage of colors (Red, Yellow, and Blue) from the thermal image is measured using the color detection method. Correspond to the color percentage, the ANFIS method predicts leakage currents from polymer insulators. Furthermore, this system interprets measured data from insulators that need to be categorized as Safe, Need Maintenance or Harmful. The final application of the system can be a non-contact tool to predict the polymer insulators used by technicians in the field.
The correlation between lightning and various weather parameters in the Padang monsoon system Ariadi Hazmi; Muhammad Imran Hamid; Rudy Fernandez; Hanalde Andre; Rizki Wahyu Pratama; Primas Emeraldi
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 1: July 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i1.pp1-9

Abstract

The correlation between lightning and several weather parameters (rainfall, humidity, air temperature, and wind) in Padang from 2016 to 2020 was statistically analyzed. Lightning data and weather parameters were obtained from two electric field mills (EFMs) and the meteorology, climatology, and geophysics agency (BMKG), Indonesia. The study results show that the highest lightning occurred in November during the wet season. The correlation coefficient between lightning and rainfall during the wet and dry seasons was 0.52 and 0.26, respectively. Furthermore, the correlation coefficient of lightning with humidity, air temperature, and wind during the wet and dry seasons was 0.25, 0.06, 0.15, and -0.45, 0.25, -0.02, respectively. These results indicate a strong relationship between lightning and rainfall during the wet season; rainfall is the only primary variable in lightning frequency.