Artificial Intelligence Techniques for Predicting the Flashover Voltage on Polluted Cup-Pin Insulators

  • Ali. A. Salem
  • R. Abd-RahmanEmail author
  • Samir A. Al-Gailani
  • M. S. Kamarudin
  • N. A. Othman
  • N. A. M. Jamail
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1073)


In this paper, flashover characteristics of polluted cup-pin insulators have investigated by means of laboratory test and a mathematical model. Data from experimental works combined with the model results from a new mathematical modelling are used to derive algorithm for Artificial Neural Network (ANN) and Adaptive Neuro-fuzzy Inference System (ANFIS) for determining the critical Flashover characteristics (current and voltage). Series of laboratory testing and measurement are carried for 1:1, 1:5, 1/10 and 1:15 ratios of top to bottom surface salt deposit density on cup and pin polluted insulators (T/B). The new model was derived based on dimensional analysis approach of the parameters which commonly effect the phenomenon of pollution flashover of insulators. This model was developed by establishment the relationship between flashover current and voltage, arc constant, arc length and layer pollution conductivity of insulator. The constant of arc A and n is determined using genetic algorithm. Comparative studies have evidently shown that the proposed AI-based technique gives the satisfactory results compared to the analytical model and test data with the coefficient of determination R-Square value more than 96%.


Outdoor insulators Artificial Neural Network Flashover Mathematical model 


  1. 1.
    Salem, A.A., Abd-rahman, R.: A review of the dynamic modelling of pollution flashover on high voltage outdoor insulators. J. Phys. Conf. Ser. 1049 (2018)Google Scholar
  2. 2.
    Ahmad, H., Abd-Rahman, R., Ahmad, M.H.: Evaluation of transmission line insulator for I-Type string insulator design. In: PECON 2016 – 2016 IEEE 6th International Conference on Power and Energy, pp. 50–53 (2017)Google Scholar
  3. 3.
    Salem, A.A., et al.: Proposal of a dynamic numerical approach in predicting flashover critical voltage, vol. 10, no. 1, pp. 51–58 (2019)Google Scholar
  4. 4.
    Salem, A.A., et al.: The effect of insulator geometrical profile on electric field distributions, vol. 14, no. 2, pp. 618–627 (2019)Google Scholar
  5. 5.
    Salem, A.A., Rahman, R.A., Kamarudin, M.S., Othman, N. A.: Factors and models of pollution flashover on high voltage outdoor insulators: review. In: 2017 IEEE Conference on Energy Conversion (CENCON), pp. 241–246 (2017)Google Scholar
  6. 6.
    IEC Std. 60507: Artificial pollution tests on high-voltage insulators to be used on AC systems (1991)Google Scholar
  7. 7.
    Dixit, P., Krishnan, V., Nagabhushana, G.R.: Studies on pollution performance of ceramic insulators under AC excitation. In: Proceedings of 16th International Symposium on High voltage Engineering (ISH 2009), 28th August 2009, Cape town, South Africa, paper NoE-35, pp. 1331–1336 (2009)Google Scholar
  8. 8.
    Wilkins, R.: Flashover voltage of high voltage insulator with uniform surface pollution films. Proc IEE 116(3), 457–465 (1969)Google Scholar
  9. 9.
    Suresh, A.G., Dixit, P.: ANN model to predict critical flashover voltages of polluted porcelain disc insulators, vol. 12, no. 11, pp. 2942–2951 (2017)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Ali. A. Salem
    • 1
  • R. Abd-Rahman
    • 1
    Email author
  • Samir A. Al-Gailani
    • 2
  • M. S. Kamarudin
    • 1
  • N. A. Othman
    • 1
  • N. A. M. Jamail
    • 1
  1. 1.University Tun Hussein Onn Malaysia (UTHM)Batu PahatMalaysia
  2. 2.School of Electric and Electronic EngineeringUniversiti Sains MalaysiaGelugorMalaysia

Personalised recommendations