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

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  • Publication
    Analysis on Multiple Acoustic and Electrical Emission of PD Signal Based on Signal to Noise Ratio (SNR) on Power Cable
    ( 2020-12-11)
    Mohammad W.N.A.W.
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Norfadilah Rosle
    ;
    Khairul Nadiah Khalid
    ;
    Afifah Shuhada Rosmi
    ;
    Ahmad Zaidi Abdullah
    ;
    Jamil M.K.M.
    Acoustic Emission (AE) and Electrical Emission (EE) partial discharge (PD) monitoring are effective methods in detection of the insulation failure in power cables. However, the unwanted noise from the surrounding environment can influence the effectiveness and accuracy of the PD measurement on the PD signal. Therefore, Discrete Wavelet Transform (DWT) denoising technique is introduced in order to suppress the disrupted noise. In this study, a different type of mother wavelet, level decomposition and its frequency spectrum on multiple AE and EE PD signals were performed via MATLAB software in order to analyze the performance of denoising technique. These PD signals were deal with white noise and Discrete spectral interference (DWT). The better performance of denoising technique is based on evaluating the maximum value of Signal to Noise Ratio (SNR) in order to find the optimum mother wavelet. In this case, the most optimum mother wavelets are rbio3.3 for AE and EE PD signals respectively with the highest value of SNR.
      4  21
  • 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.
      27  1