Thermal Image and Leakage Current Diagnostic as a Tool for Testing and Condition Monitoring of ZnO Surge Arrester

2013 ◽  
Vol 64 (4) ◽  
Author(s):  
Novizon N. ◽  
Zulkurnain Abdul Malek ◽  
Nouruddeen Bashir ◽  
N. Asilah
Keyword(s):  
Leakage Current ◽  
Condition Monitoring ◽  
Thermal Imaging ◽  
Harmonic Component ◽  
Strong Relationship ◽  
Thermal Image ◽  
Aging Condition ◽  
Third Harmonic ◽  
Surge Arresters ◽  
Thermal Data

This paper presents a study proposing a method to assess the condition of metal-oxide surge arresters. Thermal data using thermal imaging as well as the leakage current third harmonic component were used as tools to investigate the surge arrester aging condition.  Artificial Neural Network was employed to classify surge arrester condition with the temperature profile, ambient temperature and humidity as inputs and third harmonic leakage current as target. The results indicated a strong relationship between the thermal profile and leakage current of the surge arrester. This finding suggests the viability of this method in condition monitoring of surge arrester.

scholarly journals Artificial Neural Network Application for Thermal Image Based Condition Monitoring of Zinc Oxide Surge Arresters

2017 ◽  
Vol 7 (3) ◽  
pp. 593
Author(s):  
Novizon Novizon ◽  
Zulkurnain Abdul-Malek ◽  
Aulia Aulia
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Leakage Current ◽  
Thermal Image ◽  
Histogram Method ◽  
Good Tool ◽  
Third Harmonic ◽  
Surge Arresters ◽  
Long Time ◽  
Artificial Neural

<p>Manual analysis of thermal image for detecting defects and classifying of condition of surge arrester take a long time. Artificial neural network is good tool for predict and classify data. This study applied neural network for classify the degree of degradation of surge arrester. Thermal image as input of neural network was segmented using Otsu’s segmentation and histogram method to get features of thermal image. Leakage current as a target of supervise neural network was extracted and applied Fast Fourier Transform to get third harmonic of resistive leakage current. The classification results meet satisfaction with error about 3%.</p>

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

2014 ◽  
Vol 554 ◽  
pp. 598-602 ◽  
Author(s):  
Yusuf Novizon ◽  
Abdul Malek Zulkurnain ◽  
Abdul Malek Zulkurnain
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Leakage Current ◽  
Thermal Image ◽  
Critical Parameters ◽  
Thermal Images ◽  
Third Harmonic ◽  
Surge Arresters ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

The ageing level of ZnO materials in gapless surge arresters can be determined by using either the traditional leakage current measurements or recently introduced thermal images of the arrester. However, a direct correlation between arrester thermal images and its leakage current (and hence the ageing level) is yet to be established. This paper attempts to find such a correlation using an artificial neural network (ANN). Experimental work was carried out to capture both the thermal images and leakage current of 120kV rated polymeric housed gapless arresters. Critical parameters were then extracted from both the thermal image and the leakage current, before being exported into the artificial neural network tool. Using the leakage current level, the conditions of the arrester are classified as normal, caution, and faulty. The ANN correctly classifies the ageing level using only the thermal image information with an accuracy of 97%, which is highly encouraging.

scholarly journals Simulation and Experimental Investigation on Carbonized Tracking Failure of EPDM/BN-Based Electrical Insulation

Polymers ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 582 ◽  
Author(s):  
Muhammad Tariq Nazir ◽  
Faizan Tahir Butt ◽  
Bao Toan Phung ◽  
Guan Heng Yeoh ◽  
Ghulam Yasin ◽  
...  
Keyword(s):  
Leakage Current ◽  
Failure Time ◽  
Harmonic Component ◽  
Experimental Results ◽  
Shielding Effect ◽  
Surface Discharge ◽  
Melt Mixing ◽  
Electrical Field ◽  
Third Harmonic ◽  
Thermal Depolymerization

Ethylene propylene diene monomer (EPDM) is broadly employed as an insulating material for high voltage applications. Surface discharge-induced thermal depolymerization and carbon tracking adversely affect its performance. This work reports the electrical field modeling, carbon tracking lifetime, infrared thermal distribution, and leakage current development on EPDM-based insulation with the addition of nano-BN (boron nitride) contents. Melt mixing and compression molding techniques were used for the fabrication of nanocomposites. An electrical tracking resistance test was carried out as per IEC-60587. Simulation results show that contamination significantly distorted the electrical field distribution and induced dry band arcing. Experimental results indicate that electric field stress was noticed significantly higher at the intersection of insulation and edges of the area of contamination. Moreover, the field substantially intensified with the increasing voltage levels. Experimental results show improved carbonized tracking lifetime with the addition of nano-BN contents. Furthermore, surface temperature was reduced in the critical contamination flow path. The third harmonic component in the leakage current declined with the increase of the nano-BN contents. It is concluded that addition of nano-BN imparts a better tracking failure time, and this is attributed to better thermal conductivity and thermal stability, as well as an improved shielding effect to electrical discharges on the surface of nanocomposite insulators.

Surge Arrester Leakage Current Analysis by Using Particle Swarm Optimization Technique

2014 ◽  
Vol 554 ◽  
pp. 608-612
Author(s):  
Vahabi Mashak Saeed ◽  
Zulkurnain Abdul-Malek ◽  
Nabipour Afrouzi Hadi ◽  
Chin Leong Wooi ◽  
Amir Hesam Khavari
Keyword(s):  
Leakage Current ◽  
Condition Monitoring ◽  
Search Algorithm ◽  
Optimization Technique ◽  
Measurement Techniques ◽  
Particle Swarm ◽  
Operating Voltage ◽  
Surge Arresters ◽  
Particle Swarm Optimization Technique ◽  
Total Leakage

Surge arresters, as protective equipment, are used to limit any overvoltage in a power system resulting from various sources. The surge arrester affects from degradation due to the continuous operating voltage system as well as due to repeated lightning current discharge. Therefore, condition monitoring and health diagnostics of surge arresters are a necessary issue. Hence, as a feasible solution, a condition monitoring based on leakage current measurement techniques was selected to tackle the problem of age diagnostics of surge arresters. The Particle Swarm Search Algorithm was introduced as a method for extracting the third harmonic resistive component, Ir3rd, from the total leakage current. To employ this method for extracting Ir3rd, codes were developed in Matlab. The setting of Particle Swarm Search Algorithm was configured for extracting Ir3rd and accuracy of 94% was obtained.

Electrical Performance of Zinc Oxide Surge Arresters in 22 kV Distribution System Using Thermal Image Camera

2014 ◽  
Vol 931-932 ◽  
pp. 857-861
Author(s):  
Wichet Thipprasert
Keyword(s):  
Zinc Oxide ◽  
Leakage Current ◽  
Distribution System ◽  
Reducing Power ◽  
Thermal Image ◽  
Electrical Performance ◽  
Surge Arresters ◽  
Thermal Image Camera ◽  
Long Time ◽  
Image Camera

Zinc Oxide (ZnO) surge arresters (SAs) experience thermal runaway when the temperature exceeds the acceptable limit. This phenomenon is associated with the increase in resistive leakage current due to degradation. This paper presents the electrical performance of ZnO SAs in 22 kV distribution system using thermal image camera under the power frequency AC operating voltages. When ZnO surge arresters are installation takes a long time in distribution system over than 5 years. For the experimental study, as ZnO installation takes a long time over than 6 years the leakage current is 63.9 mA, temperature difference were measured over a period of time over than 14 degree Celsius. This data will be useful as a guideline for solving problems and reducing power loss from leakage current. Moreover, it will be useful in predicting lifetime of ZnO SAs.

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