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

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  • Publication
    Multiple Partial Discharge Signal Classification Using Artificial Neural Network Technique in XLPE Power Cable
    ( 2023-02-01)
    Halim M.I.A.
    ;
    Razaly N.Z.M.
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Norfadilah Rosle
    ;
    Auni W.N.
    ;
    Afifah Shuhada Rosmi
    ;
    Muhammad Zaid Aihsan
    ;
    Mohd Aminudin Jamlos
    ;
    Mas’ud A.A.
    According to partial discharge (PD) damage in the electrodes that are not entirely bridging, the presence of PD in the high voltage (HV) power cable might lead to insulation failure. PD defects can damage cross-linked polyethylene (XLPE) cables directly, which is one of the most critical electrical issues in the industry. Poor workmanship during cable jointing, aging, or exposure to the surrounding environment is the most common cause of PD in HV cable systems. As a result, the location of the PD signals that occur cannot be classified without identifying the multiple PD signals present in the cable system. In this study, the artificial neural network (ANN) based feedforward back propagation classification technique is used as a diagnostic tool thru MATLAB software in which the PD signal was approached to determine the accuracy of the location PD signal. In addition, statistical feature extraction was added to compare the accuracy of classification with the standard method. The three-point technique is also an approach used to locate PD signals in a single line 11 kV XLPE underground power cable. The results show that the statistical feature extraction had been successful classify the PD signal location with the accuracy of 80% compared to without statistical feature extraction. The distance between PD signals and the PD source affected the result of the three-point technique which proved that a lower error means a near distance between them.
  • 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
    A review of analysis of partial discharge measurements using coupling capacitor in rotating machine
    (Iran University of Science and Technology, 2025-06)
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Afifah Shuhada Rosmi
    ;
    Ayob Nazmy Nanyan
    ;
    Ahmad Syukri Abd Rahman
    ;
    Nur Dini Athirah Gazata
    ;
    Aiman Ismail Mohamed Jamil
    ;
    Mohd Helmy Halim Abdul Majid
    ;
    Normiza Masturina Samsuddin
    Partial discharge (PD) is a critical phenomenon in electrical systems, particularly in high-voltage (HV) equipment like transformers, cables, switchgear, and rotating machines. In rotating machines such as generators and motors, PD is a significant concern as it leads to insulation degradation, potentially resulting in catastrophic failure. Effective and reliable diagnostic techniques are essential for detecting and analyzing PD to ensure the operational safety and longevity of such equipment. Various PD detection methods have been developed, including coupling capacitor (CC), high-frequency current transformer (HFCT), and ultra-high frequency (UHF) techniques, each offering unique advantages in assessing the condition of HV electrical systems. Among these, coupling capacitors have gained significant attention due to their ability to improve the accuracy, sensitivity, and efficiency of PD detection in rotating machines. This study focuses on the advancements in coupling capacitor-based techniques and their critical role in enhancing PD diagnostics for monitoring and maintaining high-voltage rotating machinery.
  • Publication
    Analysis of partial discharge measurements using coupling capacitor in rotating machine
    (Iran University of Science and Technology, 2025-06)
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Afifah Shuhada Rosmi
    ;
    Ayob Nazmy Nanyan
    ;
    Ahmad Syukri Abd Rahman
    ;
    Nur Dini Athirah Gazata
    ;
    Aiman Ismail Mohamed Jamil
    ;
    Mohd Helmy Halim Abdul Majid
    ;
    Normiza Masturina Samsuddin
    Partial discharge (PD) is a significant concern in the operation of rotating machines such as generators and motors, as it can lead to insulation degradation over time, reducing the reliability and lifespan of the machines. To monitor PD activity, coupling capacitors (CC) are widely used as sensors for online PD detection, as they can effectively capture PD pulses in high-voltage (HV) rotating machines. The primary objective of this research is to measure and analyze PD signals using a CC sensor for HV rotating machines under varying input voltages and frequencies, following the guidelines of the IEC 60270 standard and utilizing the MPD 600 device. The experimental setup includes performing insulation resistance (IR) testing, PD calibration, and PD measurement. Additionally, this paper provides a detailed study of PD signal characteristics, specifically focusing on phase-resolved partial discharge (PRPD) patterns, to understand the behavior of PD in HV rotating machines, enhancing fault diagnosis and preventive maintenance strategies.
  • Publication
    Partial discharge signal measurement based on stand-alone and hybrid detection technique for power transformer
    ( 2020-01-01)
    Jalil M.A.A.
    ;
    Afifah Shuhada Rosmi
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Muzamir Isa
    ;
    Auni W.N.
    ;
    Ahmad Zaidi Abdullah
    ;
    Aizam M.T.
    Partial discharge (PD) is a phenomenon that causes failures in high voltage (HV) components due to the degradation of insulation. Before an interruption or fault occurs, early detection of insulation degradation is essential. However, the long-term effect of PD will lead to the failure of the power system. This is important to control and diagnose the health of the HV power equipment such as power transformer. The main issue when measuring PD is the accuracy and sensitivity of the PD detection technique. This paper consists of two parts which are classification of the PD detection technique and hybrid detection technique. In this paper, an overview of the detection technique for power transformer including optical detection, chemical detection, electrical detection, electromagnetic detection, acoustic emission detection and hybrid detection technique is presented. The hybrid detection technique is based on combining two or more stand-alone detection technique. Based on this review, the hybrid detection technique showed that the advantages of performance in terms of sensitivity and accuracy for detecting the PD in power transformer.
      1  36
  • Publication
    A review: Partial discharge detection using acoustic sensor on high voltage transformer
    ( 2020-01-07)
    Akashah N.A.
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Afifah Shuhada Rosmi
    ;
    Muzamir Isa
    ;
    Norfadilah Rosle
    ;
    Baharuddin Ismail
    ;
    Wooi Chin Leong
    Partial discharge (PD) is an electrical discharge which is one of the most critical breakdown factor that is affecting the electrical equipment. The loss of the power will affect consumers and system operation. High voltage (HV) transformer is one of the equipment's subjected to phenomena PD. In this paper reviews an application of acoustic methods in transformer and piezoelectric sensors application on PD detection in HV transformer. Based on this review, the new design in acoustic sensor is required in order to improve the sensitivity and bandwidth for PD detection at HV transformer. The valuable parameter such as materials, size, and PD frequency range were discussed in this paper and can be used for early stage on designing new acoustic sensor. This detection method given some benefits on preventing the power electrical system from breakdown.
      1  28
  • 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
    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 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.
      1  1