Baharuddin Ismail
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Baharuddin Ismail
Official Name
Baharuddin, Ismail
Alternative Name
Ismail, Baharuddin Bin
Ismail, Baharudidn
Ismailf, B.
Main Affiliation
Scopus Author ID
24447820000
Researcher ID
GEW-9377-2022

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  • Publication
    Influence of Electrical Tree Characterization Change Based on Tree Inception Voltage in HV Solid Insulation
    ( 2023-01-01)
    Abdulah C.S.K.
    ;
    Rosmi A.S.
    ;
    Isa M.A.M.
    ;
    Baharuddin Ismail
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Wan Azani Wan Mustafa
    ;
    Kamarol M.
    ;
    Yii C.C.
    ;
    Al-Attabi K.
    ;
    Almoussawi Z.A.
    To improve accuracy of degradation diagnosis for HV solid insulation, it is important to clarify the mechanism of inception and characterization of electrical-tree. In this paper, the study of influence between TIV and electrical tree characterization was done in a laboratory experiment by monitoring the TIV values and electrical tree propagation. This experiment involve using charged couple device camera (CCD) to capture and record the electrical tree thorough the experiment, a microscope to enlarge the needle tip that was inserted into the XLPE sample, and finally a personal computer to display the whole treeing growth process. Then, the voltage was injected into sample of XPLE constantly until the electrical tree start to initiate at the needle tip. As a result, the electrical tree take form based on the TIV, small number of TIV produce a less dense electrical tree compare to higher value of TIV. Additionally, denser electrical tree propagates faster and may lead to early breakdown.
  • Publication
    Review of Edge-based Image Segmentation on Electrical Tree Classification in Cross-linked Polyethylene (XLPE) Insulation
    ( 2021-06-11)
    Mohd Annuar Mohd Isa
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Baharuddin Ismail
    ;
    Afifah Shuhada Rosmi
    ;
    Isa M.
    ;
    Wan Azani Wan Mustafa
    ;
    Kamarol M.
    ;
    Mansor N.S.
    ;
    Nazar N.S.M.
    Electrical trees are the degradation events most linked with partial discharge (PD) activity in cross-linked polyethylene (XLPE) insulation of high voltage (HV) cables. To investigate tree structures and forms, study of electrical tree structures for morphological analysis often carried out using optical microscopy. However, since the noise induced by the occlusion and illumination, as well as by non-uniform intensity either from optical device's setting or the non-standard readout procedure, causes the deterioration of the original microscopy images, resulting in critically loses of information pertaining the tree structures making it difficult to obtained accurate measurement. Image segmentation is one of the potential solutions as it is well-suited for extracting information or certain features from microscopy images. This paper provides review of several segmentation techniques applied on the classification of electrical tree image acquired through lab environment. The works can be separated into three stages. The first step includes the preparation of samples and collection of treeing images by means of real-time microscopy observations. The captured data would then be pre-processed to achieve image binarization. In the next step, image segmentation process is conducted using existing edge-based segmentation methods including Prewitt, Roberts, Canny and Kirsch's templates. Later, comparative analysis will be performed using IQA (image quality assessment) metrics of accuracy, sensitivity, specificity, false-positive-rate and the Matthews Correlation Coefficient (MCC) as the final step. Performance-wise indicates that Kirsch's template able to segment most of the treeing pixels with accuracy of 97.63%, 63% sensitivity, 98.18% specificity and 0.46 MCC while showing low pixels misclassification. This result provides better justification for the integration of the edge-based technique in developing image segmentation algorithm well-matched for the electrical tree analysis in the future.
      36  1
  • Publication
    Electrical Tree Investigation on Solid Insulation for High Voltage Applications
    ( 2021-01-01)
    Abdulah C.S.K.
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Baharuddin Ismail
    ;
    Isa M.A.M.
    ;
    Afifah Shuhada Rosmi
    ;
    Wan Azani Wan Mustafa
    ;
    Kamarol M.
    Electrical treeing is a major cause of a breakdown in solid insulation cable. This phenomenon reduced aging by degrading the insulation, leading to failure in the high voltage materials. The most common experimental set-up in studying the electrical tree is using a needle electrode to initiate the treeing image. Different types of needle and insulation material had been studied from the previous experiment. This paper review the method used to investigate tree growth and its technique to capture the treeing image. Based on this review, several causes delay the treeing process in the needle embedded experiments. In contrast, 2D image processing is the most frequent image developed in the electrical tree on solid insulation.
      8  35
  • Publication
    Modelling of piezoelectric sensor based on ZnO material for partial discharge detection on power transformer
    ( 2020-01-01)
    Akashah N.A.
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Afifah Shuhada Rosmi
    ;
    Muzamir Isa
    ;
    Baharuddin Ismail
    ;
    Kamarol M.
    ;
    Roslizan N.D.
    ;
    Khairul Nadiah Khalid
    Detection of partial discharge (PD) in early stages able to reduce the risk of decommissioning of high voltage (HV) equipment. However, the conventional method for PD detection are not suitable for on-site measurement due to electrical disturbance. One of the method in detecting PD signal is piezoelectric based acoustic emission (AE) sensors. In this project, an AE sensor is modelled to obtain a PD signal in the range of 10 – 300 kHz occurred in HV transformer and been found out by simulation and analytical approach. Two models of a piezoelectric sensor with different types of cantilever and different dimension variation starting from 4 mm to 15 mm are designed in the Finite element Method (FEM) in order to investigate the resonant frequency which is matched to the range of AE detection. Zinc oxide (ZnO) as a piezoelectric material is proposed in this project due to its high piezoelectric coupling and environmentally friendly compared to the others material which is harmful. Based on the simulation result, ZnO piezoelectric sensor with the length of 5 mm and thickness of 0.451 mm generates 0.0537 mV electrical potentials under the resonant frequency of 155.30 kHz which is in the range of AE detection technique.
      31  3