Afifah Shuhada Rosmi
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Preferred name
Afifah Shuhada Rosmi
Official Name
Afifah Shuhada, Rosmi
Alternative Name
Rosmi, Afifah Shuhada
Rosmi, Afifah Shuhada C
Rosmi, A. S.
Rosmi, A. S.C.
Main Affiliation
Scopus Author ID
57193830914
Researcher ID
DNN-7471-2022

Research Output
Now showing 1 - 3 of 3
  • 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
    Electrical tree image de-noising using threshold wavelet transform and wiener filter
    (Semarak Ilmu Publishing, 2025)
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Cik Siti Khadijah Abdulah
    ;
    Nur Dini Athirah Gazata
    ;
    Mohd Anuar Mohd Isa
    ;
    Baharuddin Ismail
    ;
    Mohamad Kamarol Jamil
    ;
    Afifah Shuhada Rosmi
    ;
    Firdaus Muhammad-Sukki
    ;
    Abdullahi A. Mas’ud
    ;
    Noor Syazwani Mansor
    Electrical treeing occurred in solid dielectric materials, especially in electrical application with high voltage. The occurrence of electrical tree happens when high electric fields applied, causing tiny channels or paths to form. The main issue during the data collection process is the changes of lighting, making it difficult to study the tree's propagation length, fractal dimension, and growth rate due to corrupted images. This research aims to analyse electrical tree structure images in XLPE material using a CCD camera and develop image de-noising techniques to suppress noise on the electrical tree image. The performance was then analysed using the Otsu thresholding algorithm for accurate segmentation. The methodology was divided into four phases: sample preparation, experimental setup, image pre-processing in MATLAB, and testing four de-noising filters: Wiener, median, NLM, and Gaussian. The Wiener filter with higher PSNR, SNR, and RMSE was selected and using superimposed method, both threshold wavelet transforms and wiener was combined to eliminate the noise. Finally, the proposed method of superimposed was tested with the Otsu thresholding method to evaluate accuracy, sensitivity, and specificity of the combination filter. Based on the analysis of PSNR, SNR, and RMSE, the performance of the threshold wavelet and Wiener filter (TWWF) de-noising technique improves the image quality of the electrical tree structure. Thus, for the Otsu thresholding segmentation algorithm analysis, it also had the highest values in terms of accuracy, sensitivity, and specificity.
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