Fractal Hilbert Sensor to Detect Partial Discharge on Transformer

Authors

  • H H Sinaga Department of Electrical Engineering, Faculty of Engineering, Universitas Lampung, Jalan Prof. Soemantri Brojonegoro No. 1, Bandar Lampung, 35143 Indonesia
  • H B H Sitorus Department of Electrical Engineering, Faculty of Engineering, Universitas Lampung, Jalan Prof. Soemantri Brojonegoro No. 1, Bandar Lampung, 35143 Indonesia
  • D Permata Department of Electrical Engineering, Faculty of Engineering, Universitas Lampung, Jalan Prof. Soemantri Brojonegoro No. 1, Bandar Lampung, 35143 Indonesia
  • N Soedjarwanto Department of Electrical Engineering, Faculty of Engineering, Universitas Lampung, Jalan Prof. Soemantri Brojonegoro No. 1, Bandar Lampung, 35143 Indonesia

DOI:

https://doi.org/10.23960/jesr.v1i2.31 - Abstract View: 283

Keywords:

partial discharge, Fractal Hilbert Sensor, sensor sensitivity

Abstract

The design of fractal Hilbert sensor is presented in this paper. The sensor is intended to detect partial discharge (PD) in transformer insulation. The fractal Hilbert sensor designed using 4 order fractal and etching on single layer PCB board. The Hilbert fractal type is chosen as this type of sensor can be built on smaller area compare to other types. The sensor overall dimension is limited to 5x5 cm as it is proposed to be use to detect the PD presence in transformer. The sensor sensitivity is tested using a closed type TEM cell. After the sensitivity of the sensor is tested the sensor then applied to detect the PD signals emitted by void PD defect model. The results show the sensor has sensitivity as high as 10 dB. The sensor also has capability to detect the PD signals generated by the PD defect source. The waveforms captured by the sensor show the sensors can capture high frequency pulse generated by the PD source

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Published

2020-12-17

How to Cite

[1]
H. H. . Sinaga, H. B. H. . Sitorus, D. Permata, and N. Soedjarwanto, “Fractal Hilbert Sensor to Detect Partial Discharge on Transformer”, JESR, vol. 1, no. 2, pp. 94–100, Dec. 2020.

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Articles