Nur Adyani Mohd Affendi
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Nur Adyani Mohd Affendi
Official Name
Nur Adyani, Mohd Affendi
Alternative Name
Mohd Affendi, Nur Adyani
Mohd Affendi, Nur Adyani
Mohd Affendi, Nur Adyani
Affendi, N. A.Mohd
Affendi, Nur A.M.
Affendi, N. A.M.
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Scopus Author ID
55480876600

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  • Publication
    Arcing fault diagnosis using first peak arrival of EM radiation signal
    ( 2021-06-11)
    Melaty binti Amirruddin
    ;
    Mohd Rafi Adzman
    ;
    Nur Adyani Mohd Affendi
    ;
    Azralmukmin Azmi
    ;
    Muhd Hafizi Idris
    ;
    Hana Abdull Halim
    ;
    Muzamir Isa
    ;
    Halim S.A.
    The objective of this study was to diagnose the arcing fault signals based on the first peak of arrival method using antenna to assess its use as potential arcing fault detection in power system network. Square patch antenna and circle patch antenna were employed for detection on artificial arcing in real environment. First peak of arcing signal arrival was measured through an analysis over a range of time and amplitude signals detected. For accurate results, Discrete Wavelet Transform (DWT) denoising technique was applied to the arcing signals detected as denoising tools. Analysis of first peak of signal arrival time and amplitude were carried out using MATLAB software to measure the changes in signals detected caused by di different placements of antenna. The results revealed that the first peak of signal arrival time, amplitude, type of antenna used and placement of the antenna around arcing source point all reflect the signals measurement.
      3  5
  • Publication
    Arcing fault diagnosis using enhanced cross-correlation technique
    ( 2022-01-01)
    Melaty binti Amirruddin
    ;
    Mohd Rafi Adzman
    ;
    Nur Adyani Mohd Affendi
    ;
    Muhd Hafizi Idris
    ;
    Syahirah Abd Halim
    This study explored the potential use of cross-correlation as a technique for detecting arcing faults in a power system distribution network. The cross-correlation technique was employed to investigate the effect of each antenna placement as a detection device, time difference of arrival (TDOA), time delay, and correlation magnitude of arcing signals detected during on-line arcing fault measurement. The arcing fault was detected using four antennas that had been set up around the arc source point in a high voltage (HV) laboratory. The measurements were taken using a digital oscilloscope. For precise results, the Discrete Wavelet Transform (DWT) denoising technique combined with cross-correlation (CC) technique were applied using MATLAB software to identify the arcing signals detected in order to diagnose the differentiation between noisy and real arcing fault signals. Further assessment was carried out by performing a cross-correlation technique on the real arcing signals obtained to find the similarities and arrival time's delay between single arcing signals' placement. The outcome shows that all measurements including the time difference of arrival (TDOA), correlation magnitude, time delay, and antennas' placement towards the arcing source point are valuable in determining the arcing signals detected precisely.