TY - GEN
T1 - Wavelet Transformation Selection for Detection of Ferroresonance Behaviour
AU - Negara, I. Made Yulistya
AU - Asfani, Dimas Anton
AU - Hernanda, I. Gusti Ngurah Satriyadi
AU - Fahmi, Daniar
AU - Verdiansyah,
AU - Aji, Bagas Kuntala
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - Ferroresonance is a nonlinear resonance phenomenon that can cause a high increase in current and voltage so that it can cause damage to electrical equipment and can eventually disrupt the electrical system. The main problem in this phenomenon is the complexity of this phenomenon in its detection, prevention, and handling. Wavelet transformation is one of the methods for analyzing ferroresonance detection. The purpose of this study is to be able to find out the suitable wavelet transformation based to detect ferroresonance phenomena. In this study, the detection was carried out by analyzing significant changes in the detailed coefficient value of wavelet (DWT) ferroresonance signal using the MATLAB software. The choice of based wavelet is done by two methods. The first method is to analyze the speed of detection and the ratio of the detail coefficient value detected to the threshold value. The second method is to compare the ratio of cumulative energy calculations to normal conditions and ferroresonance conditions. The based wavelet used 54 based wavelet available on the MATLAB software DWT. Based on studies conducted in the first method, the coif5 mother wavelet shows superior detection performance compared to other mother wavelets by detecting faster consistently in each ferroresonance mode. In the second method, the rbio3.3 mother wavelet consistently produces a cumulative energy ratio greater than the other mother wavelets.
AB - Ferroresonance is a nonlinear resonance phenomenon that can cause a high increase in current and voltage so that it can cause damage to electrical equipment and can eventually disrupt the electrical system. The main problem in this phenomenon is the complexity of this phenomenon in its detection, prevention, and handling. Wavelet transformation is one of the methods for analyzing ferroresonance detection. The purpose of this study is to be able to find out the suitable wavelet transformation based to detect ferroresonance phenomena. In this study, the detection was carried out by analyzing significant changes in the detailed coefficient value of wavelet (DWT) ferroresonance signal using the MATLAB software. The choice of based wavelet is done by two methods. The first method is to analyze the speed of detection and the ratio of the detail coefficient value detected to the threshold value. The second method is to compare the ratio of cumulative energy calculations to normal conditions and ferroresonance conditions. The based wavelet used 54 based wavelet available on the MATLAB software DWT. Based on studies conducted in the first method, the coif5 mother wavelet shows superior detection performance compared to other mother wavelets by detecting faster consistently in each ferroresonance mode. In the second method, the rbio3.3 mother wavelet consistently produces a cumulative energy ratio greater than the other mother wavelets.
KW - Ferroresonance
KW - Mother Wavelet
KW - Wavelet Discrete Transformation
UR - http://www.scopus.com/inward/record.url?scp=85078490286&partnerID=8YFLogxK
U2 - 10.1109/ISITIA.2019.8937175
DO - 10.1109/ISITIA.2019.8937175
M3 - Conference contribution
AN - SCOPUS:85078490286
T3 - Proceedings - 2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019
SP - 253
EP - 258
BT - Proceedings - 2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019
Y2 - 28 August 2019 through 29 August 2019
ER -