Haziah Abdul Hamid
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Preferred name
Haziah Abdul Hamid
Official Name
Abdul Hamid, Haziah
Alternative Name
Hamid, Haziah
Hamid, H.
Hamid, H. A
Abdul Hamid, H.
Hamid, Haziah Abdul
Hamid, Haziah Binti Abd
Main Affiliation
Scopus Author ID
57213599593
Researcher ID
HLX-4281-2023

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  • Publication
    An alternative approaches to predict flashover voltage on polluted outdoor insulators using artificial intelligence techniques
    ( 2020-04-01)
    Salem, Ali. Ahmed. Ali
    ;
    Rahman, Rahisman Abd
    ;
    Kamarudin M.S.
    ;
    Othman, Nordiana Azlin
    ;
    Jamail, Nor. Akmal. Mohd.
    ;
    Haziah Abdul Hamid
    ;
    Ishak, Mohd. Taufiq
    This paper presents an alternative approach for predicting critical voltage of pollution flashover by using Artificial Intelligence (AI) technique. Data from experimental works combined with the theoretical results from well-known theoretical modelling are used to derive algorithm for Artificial Neural Network (ANN) and Adaptive Neuro-fuzzy Inference System (ANFIS) for determining critical voltage of flashover. Series of laboratory testing and measurement are carried for 1:1, 1:5 and 1:10 ratios of top to bottom surface salt deposit density on cup and pin insulators. Insulators variables such as height H, diameter D, form factor F, creepage distance L, equivalent salt deposit density (ESDD) and flashover voltage correction are identified and used to train the AI network. Comparative studies have evidently shown that the proposed (AI) technique gives the satisfactory results compared to the analytical model and test data with the Coefficient of determination R-Square value of more than 97%.
      4  3
  • Publication
    Flashover voltage prediction on polluted cup-pin the insulators under polluted conditions
    ( 2021-01-01)
    Salem A.A.
    ;
    Abd-Rahman R.
    ;
    Kamarudin M.S.
    ;
    Othman N.A.
    ;
    Jamail N.A.M.
    ;
    Nuriziani Hussin
    ;
    Haziah Abdul Hamid
    ;
    Rawi I.M.
    The natural pollution which is mainly affected by the weather conditions are the main cause of flashovers on high voltage insulators leading to outages in power systems. In this work, characteristics of flashover for contaminated cup-pin insulators have been studied based on experiential test and a mathematical model. Information from laboratory test combined with new mathematical model results are used to define Artificial Neural Network (ANN) algorithm and Adaptive Neuro-fuzzy Inference System (ANFIS) for calculated the flashover characteristics (current IF and voltage UF). several of experiments and measurement are carried out for 1:1, 5:1, 10:1 and 15:1 ratios of bottom to top surface salt deposit density on contaminated samples (z). Dimensional Analysis Method (DAM) was used to derive new model for the variables which often effective in the flashover phenomenon of polluted insulators. The model was derived by establishment the relationship between flashover voltage UF and current IF, length of pollution layer LP, exposure time t, arc constant A and layer pollution conductivity of insulator σ. The both arc constants A and n is computed using genetic algorithm. Comparative investigates have clearly shown that the approach AI-based method gives the agreeable results compared to the mathematical model.
      6  2