Norfadilah Rosle
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Preferred name
Norfadilah Rosle
Official Name
Norfadilah, Rosle
Alternative Name
Rosle, N.
Rosle, N. F.
Rosle, Norfadilah
Main Affiliation
Scopus Author ID
57208407506
Researcher ID
DRD-5901-2022

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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
    Simulation study on photovoltaic panel temperature under different solar radiation using computational fluid dynamic method
    ( 2020-01-07)
    Leow W.Z.
    ;
    Mohd Irwan Yusoff
    ;
    Safwati Ibrahim
    ;
    Muhammad Irwanto Misrun
    ;
    Amelia A.R.
    ;
    Syafiqah Z.
    ;
    Muhammad Izuan Fahmi Romli
    ;
    Norfadilah Rosle
    The electrical production is the primary performance of any solar photovoltaic (PV) system. The PV panel operating temperature is inversely proportional to the electrical production of the PV panel. The operating temperature of PV panel is influenced by solar radiation absorbed and the ambient temperature. In the present work, Computational Fluid Dynamics (CFD) method is used to investigate a three-dimensional (3-D) model of a PV panel. It is also essential to estimate the thermal behaviour of the PV panel under various environmental conditions. The primary purpose of this current work is to analyse temperature distribution from the PV panel under given operating conditions. The model geometry is built by using CATIA design software. ANSYS software was simulated the different intensity of solar radiation that applied to the PV panel in order to observe the temperature distribution on each layers of the PV panel. The ambient temperature of the simulation is fixed 35C according to the maximum ambient temperature captured in Malaysia. The simulation results show that an increase in solar radiation intensity along with the PV panel operating temperature increase.
  • Publication
    Improvement of electrical power system dynamic stability using Riccati Matrix method
    ( 2015)
    Norfadilah Rosle
    Low frequency oscillations appear when a small disturbance occurs in an interconnected multi-machine power system and becomes one of the major subjects concerning in power system studies. Due to small disturbances, power systems experience these poorly damped low-frequency oscillations. In the dynamic electrical power system stability, the positive damping oscillation is very important. By using the optimum gains that obtained from Riccati matrix method, these oscillations can be well damped and hence the system stability is enhanced. Riccati matrix method is used to enhance better system stability in damping oscillation power system. This research presents a design of a single machine to an infinite bus (SMIB) with additional optimum gain from Riccati matrix method to enhance the dynamic stability of power systems by improving the damping of the low frequency oscillations. Eigenvalues analysis and time domain analysis are applied to the overall system. MATLAB Simulink is used to design a Riccati matrix method to enhance the damping characteristic of power system to improve its stability. The dynamic simulations results are presented to show the effectiveness and robustness of the designed Riccati matrix method. Analysis and simulation have proved the effectiveness of a Riccati matrix method in order to improve the electrical power system dynamic stability.
  • 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.
  • 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
    ;
    Abdullah A.Z.
    ;
    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.