Baharuddin Ismail
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Preferred name
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
    Performance evaluation of Edge-based segmentation methods for electrical tree image analysis in high-voltage experiments
    (Semarak Ilmu Publishing, 2025-06)
    Mohd Annuar Mohd Isa
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Afifah Shuhada Rosmi
    ;
    Baharuddin Ismail
    ;
    Mohamad Firdaus Azahari
    ;
    Mohamad Kamarol Jamil
    ;
    Noor Syazwani Mansor
    ;
    Abdullahi A. Mas’ud
    ;
    Firdaus Muhammad-Sukki
    This research evaluates the performance of edge-based segmentation methods in analysing two-dimensional (2D) electrical tree images obtained during high-voltage (HV) electrical tree experiments. Non-uniform illumination in 2D optical images poses challenges in accurately extracting and measuring the original treeing image. Edge segmentation emerges as a promising solution to precisely distinguish tree structures from the insulation background within the image. Cross-linked polyethylene (XLPE) samples were subjected to HV stress for real-time propagation observation, followed by extraction and segmentation of treeing images using edge-based operators. The findings emphasize the superiority of the Roberts edge operator in accurately detecting electrical trees, showcasing the highest average accuracy of 97.01% and 99.58% specificity, while also demonstrating relatively high sensitivity. Moreover, the Roberts method provide much precisely measures the propagation length and width than conventional measurement method, closely approximating the actual tree measurements. This research emphasizes the significance of accurate segmentation for investigating electrical tree propagation in XLPE materials and provides recommendations for future research, especially in HV XLPE cable manufacturing.
  • Publication
    Analysis of array UHF sensor for partial discharge detection in power transformer
    (Semarak Ilmu Publishing, 2025-08)
    Nur Dayini Roslizan
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Afifah Shuhada Rosmi
    ;
    Baharuddin Ismail
    ;
    Mohd Aminudin Jamlos
    ;
    Raimi Dewan
    Partial discharges (PD) are small electrical discharges that occur within insulation materials and can lead to equipment failure and safety hazards. The Ultra High Frequency (UHF) sensor consists of a broadband antenna and a UHF receiver, which are designed to detect and analyse the electromagnetic emissions from partial discharges. This paper presents the design and characterization of the 4th order Hilbert fractal UHF sensor for PD detection in power transformer. The sensor is designed to operate in the frequency range of 300 MHz to 3 GHz and is optimized for high gain and directivity. The performance of the sensor is evaluated using simulation and measurement techniques. Simulation results show that the sensor has directivity of 7.9 dBi and reflection coefficient below -10 dB with VSWR ≤ 5.
  • Publication
    Image de-noising based on WMF technique for electrical trees structure in high voltage cable insulation
    (Semarak Ilmu Publishing, 2025-11)
    Siti Khadijah Za'aba
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Baharuddin Ismail
    ;
    Afifah Shuhada Rosmi
    Electrical treeing is a common problem during the pre-breakdown phenomenon in solid insulations due to the damage caused by Partial Discharge (PD) that progresses through stressed insulation via chemical degradation, which resembles the shape of a tree root. This resulted in a decrease in performance through degrading the insulation, which became a serious problem while dealing with electrical equipment. Hence, a deep understanding of electrical tree structure is vital to improving the quality of solid insulations. Ergo, optical microscopy is primarily used to examine tree structures, shapes, and fractal dimensions to reconstruct electrical tree structures for morphological study. However, optical microscopy images are frequently degraded by noise from readout procedures or image data acquisition systems, noise caused by occlusion, illumination, non-uniform intensity, destroying potential tree pixels, and a critical loss of information about the electrical tree structures. Therefore, this research proposed the Wiener Median Fusion (WMF) filter for electrical tree study. The performance of the WMF de-noising technique improves the image quality for the precise portrayal of the electrical tree structure based on thresholding segmentation algorithm analysis in terms of accuracy, sensitivity, and false positive rate. Based on the analysis of the thresholding segmentation algorithm, Otsu's thresholding exhibits the highest result compared to Niblack. The Otsu's overall percentage in terms of accuracy is 80.2934%, the sensitivity is 99.1513%, and the false positive rate is 82.6265%.
      1  2
  • Publication
    Analysis of acoustic sensor placement for PD location in power transformer
    (Scientific and Technological Research Council of Türkiye (TÜBİTAK), 2020)
    Khairul Nadiah Khalid
    ;
    Rohani, Muhammad Nur Khairul Hafizi
    ;
    Chai Chang YII
    ;
    Baharuddin Ismail
    ;
    Muzamir Isa
    ;
    Wan Nurul Auni Wan Muhammad
    Partial discharge (PD) is an abnormal activity that occurs in high-voltage components, such as power cables, switchgear, machines, and power transformers. Such activity needs to be diagnosed for the equipment to last longer as PD could harm the insulation and potentially lead to asset destruction from time to time. Moving one or more externally mounted acoustic sensors to different locations on the transformer tank is commonly used in order to detect and locate PD signal occurring in the power transformer. However, this procedure may lead to less accuracy in PD identification. Therefore, this research paper presents an analysis of acoustic sensor placement based on time of arrival (TOA) technique for PD location in a power transformer. The detection and location can be determined by permanently installing the acoustic sensor to provide valuable data in an early stage of occurrence for online condition PD monitoring. Several methods are available for the detection of PD signal, whereby one of the best choices is via acoustic emission (AE). PD creates an ultrasonic signal used for PD detection. This paper proposes the possible placement of AE sensors to be mounted on the power transformer wall based on ideal and static PD signals. The sensors were placed in order to capture the PD signal without any disturbance signal from inside or outside the tank. The time for the signal for the first approach for each sensor is recorded to estimate the PD location using the TOA technique. A comparison between the least square method (LSM) and Gauss-Jordan elimination (GJE) for the TOA technique was analyzed to differentiate the resulting performance. This research utilized three different PD sources to apply the performance analysis on PD locations, while five cases were proposed to represent the five different placements of four sensors for the analysis. This research ultimately suggests that sensors be placed and randomly mounted on the four sides of the transformer tank, with one sensor allocated to one side. Among all five cases, Case 1 and Case 5 yielded a displacement error (DE) less than others, while between these two cases, Case 5 gave the lowest DE. The findings were recorded based on LSM and GJE methods used to differentiate the resulting performance.
      1  6
  • Publication
    Influence of PD source and AE sensor distance towards arrival time of propagation wave in power transformer
    ( 2020-01-07)
    Khairul Nadiah Khalid
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Baharuddin Ismail
    ;
    Muzamir Isa
    ;
    Afifah Shuhada Rosmi
    ;
    Wooi Chin Leong
    ;
    Yii C.C.
    Partial discharge (PD) often begins with cracks or gas-filled voids in solid insulation or with gaseous bubbles in liquid insulation. These presences can degrade the quality of insulator. PD detection can identify these cracks at high voltage equipment such as power cables and power transformer at the early stage. One of PD detection methods is acoustic emission (AE) detection. PD produces an ultrasonic signal that can be captured by an AE sensor. The signal captured is then analysed by capturing the time of the receiving signal onto the sensor. The information related to time can be used for allocating the PD for maintenance purpose. This paper shows the influence of the distance between PD source and the AE sensor towards the arrival time of propagation wave in power transformer. In this study, the four placements of sensors were analysed by having three possible PD sources to represent the variety of distances between the PD source and the sensor. The simulated signal is generated by MATLAB and the arrival time is captured using time of arrival (TOA) method. The time captured and the distance between the PD source and arrival time showed that the relationship is proportional to one another.
      40  1