Correlation between Third Harmonic Leakage Current and Thermography Image of Zinc Oxide Surge Arrester for Fault Monitoring Using Artificial Neural Network

Novizon, Yusuf; Abdul‐Malek, Zulkurnain

doi:10.4028/www.scientific.net/amm.554.598

Cited by 13 publications

(7 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Degraded operation of the arrester may result in a malfunction of the arrester protection of the equipment [11,12]. The degradation of the polymer insulated ZnO arrester is a reduction in the weight and length of the polymer molecule which can change the properties of the polymer material due to a reaction that causes the breaking of the main molecular bond chain [18].…”

Section: Zno Surge Arrester Degradationmentioning

confidence: 99%

External Leakage Current Separation to Determine Arrester Condition Due to Contamination

Novizon,

Mondrizal,

Darwison

et al. 2023

JNTE

View full text Add to dashboard Cite

Leakage current measurements can be used to determine the aging condition of the ZnO arrester. The leakage current that occurs in the arrester is divided into two, namely external and internal leakage currents. The external leakage current is affected by contamination and the internal leakage current is affected by the aging of the varistor in the arrester. The external and internal leakage currents are measured separately to determine their contribution to the arrester condition. In this study, the effect of salt contamination on the arrester was studied further. The level of contamination used consisted of low, medium and heavy. The obtained leakage current is analyzed using wavelet energy. The results of this study indicate that the wavelet energy of each leakage current is different and can be used as an indicator in further analysis. The conclusion obtained is that the external leakage current is affected by contamination and has a different energy with the internal leakage current due to aging of the varistor arrester components.

show abstract

Section: Zno Surge Arrester Degradationmentioning

confidence: 99%

External Leakage Current Separation to Determine Arrester Condition Due to Contamination

Novizon,

Mondrizal,

Darwison

et al. 2023

JNTE

View full text Add to dashboard Cite

show abstract

“…4) Detection of leakage current in materials of solar cells [27]. 5) Determine ageing of ZnO materials in gapless surge arresters [28]. 6) Diagnose leakage current of extremely low value by induced temperature variations down to 10 µK at a lateral resolution down to 5 µm [29].…”

Section: Irt In Tracing Root Cause Of Leakage Currentmentioning

confidence: 99%

Quantitative Infrared Thermography Resolved Leakage Current Problem in Cathodic Protection System

Shariff¹

2019

IJATCSE

View full text Add to dashboard Cite

Leakage current problem can happen in Cathodic Protection (CP) system installation. It could affect the performance of underground facilities such as piping, building structure, and earthing system. Worse can happen is rapid corrosion where disturbance to plant operation plus expensive maintenance cost. Occasionally, if it seems, tracing its root cause could be tedious. The traditional method called line current measurement is still valid effective. It involves isolating one by one of the affected underground structures. The recent methods are Close Interval Potential Survey and Pipeline Current Mapper were better and faster. On top of the mentioned method, there is a need to enhance further by synthesizing with the latest visual methods. Therefore, this paper describes research works on Infrared Thermography Quantitative (IRTQ) method as resolution of leakage current problem in CP system. The scope of study merely focuses on tracing the root cause of leakage current occurring at the CP system lube base oil plant. The results of experiment adherence to the hypothesis drawn. Consequently, resolve the problem and recommend betterment for the future.

show abstract

“…Some of them are based on on-line monitoring while the others investigate off-line monitoring procedures. Newly developed MOSA monitoring methods are based on artificial intelligence [1][2][3][4][5][6]. Most researches propose the measurement of leakage current in order to extract MOSA's condition indicators [7][8][9][10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Machine Learning MOSA Monitoring System

Manjunath,

Vrtagić,

Dogan

et al. 2021

I2M

View full text Add to dashboard Cite

This research paper deals with the problem of Metal-Oxide Surge Arrester (MOSA) condition monitoring and a new methodology in surge arrester monitoring and diagnostics is presented. A machine learning algorithm (back propagation regression) is used to estimate the non-linearity coefficient of the surge arrester, based on operating voltage and leakage current of the arrester. Using a simulated system, this research investigates the possibility of application and efficiency of machine learning. It is shown that the applied learning algorithm results are competitive with the model results parameters calculated as R2 = 0.999 and mean absolute real error computed as 0.005 which has shown that the proposed model can be used for MOSA monitoring and diagnostic purposes.

show abstract

Correlation between Third Harmonic Leakage Current and Thermography Image of Zinc Oxide Surge Arrester for Fault Monitoring Using Artificial Neural Network

Cited by 13 publications

References 17 publications

External Leakage Current Separation to Determine Arrester Condition Due to Contamination

External Leakage Current Separation to Determine Arrester Condition Due to Contamination

Quantitative Infrared Thermography Resolved Leakage Current Problem in Cathodic Protection System

Machine Learning MOSA Monitoring System

Contact Info

Product

Resources

About