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
    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.
  • 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
    UHF Sensors for On-line Partial Discharge Detection on Power Transformer: Hilbert fractal, Moore Fractal and Peano fractal
    ( 2020-12-11)
    Abd Jalil M.A.
    ;
    Afifah Shuhada Rosmi
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Muzamir Isa
    ;
    Roslizan N.D.
    ;
    Leow W.Z.
    ;
    Mohd Aminudin Jamlos
    Partial discharge (PD) is the causes of the fault to occur in high voltage equipment due to the breakdown of the insulation system happen on equipment, even old equipment or new equipment. The PD in transformer oil is one of the significant causes of insulation failure and a breakdown. Hence, a sensor is needed to continuously monitor and detect the PD at an early stage on the power transformer. An antenna is one of the sensors that can be used to detect PD based on ultra-high frequency (UHF) method. However, the size of the antenna is the main problem to be installed in the transformer tank. Thus, three types of antenna which are Moore, Hilbert and Peano fractal with the dimension of 10 X 10 cm is designed to operate in UHF range 0.3 GHz to 3 GHz to be able to detect the frequency of partial discharge signal generated by electromagnetic waves. The performance of the proposed antennas in terms of return loss, Voltage Standing Wave Ratio (VSWR) and radiation pattern are analysed and compared for PD detection on the power transformer. Based on the result, the fourth-order of Hilbert fractal antenna was found to be the best antenna for PD detection in power transformer at working frequency range from 0.72 GHz to 2.77 GHz. This antenna also has low threshold of return loss at-36.2 dB for the resonant frequency at 1.67 GHz and the value of VSWR is near to one which is 1.03. Lastly, the radiation pattern of this antenna is almost in hemisphere shape and the gain variation of all frequencies are nearly stable compared to the other types of antenna.
  • Publication
    Comparison Study of UHF Sensor Modelling Based on 4th Order Hilbert Fractal Category for Partial Discharge Detection in Power Transformer
    ( 2020-12-11)
    Roslizan N.D.
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Afifah Shuhada Rosmi
    ;
    Baharuddin Ismail
    ;
    Mohd Aminudin Jamlos
    ;
    Wooi Chin Leong
    ;
    Che Muhammad Nor Che Isa
    ;
    Jalil M.A.A.
    PD detection is an effective method of inspecting insulation defects and identifying potential faults in a power transformer. Electromagnetic waves generated due to PD can be detected by ultrahigh-frequency (UHF) sensor in the frequency band greater than 300 MHz. However, the size and the frequency bandwidth of a UHF sensor for PD detection are the concern for practical installation inside a transformer. High sensitivity and wide bandwidth of sensors are needed in order to detect the PD signal at an early stage. This paper presents an array with partial ground 4th order Hilbert fractal UHF sensor for PD detection inside a power transformer. This UHF sensor was modeled to capture PD signal in a range of frequencies between 300 MHz to 3 GHz. The sensor is designed by using CST software where the transmission lines combined 2 sensors become 1 output by setting the dimension of 100 x 200 mm for length and width with an FR4 epoxy substrate of thickness 1.6 mm. Based on the simulation result, the proposed sensor is obtained a PD signal measurement with a reflection coefficient below-10 dB with VSWR ?5. The advantages of this sensor have a wide bandwidth, high sensitivity and suitable size for easy installation. Thus, this sensor has been qualified as UHF PD detection in the power transformer.
  • Publication
    A Review: Partial Discharge Detection using UHF sensor on High Voltage Equipment
    ( 2020-01-07)
    Roslizan N.D.
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Wooi Chin Leong
    ;
    Isa M.
    ;
    Baharuddin Ismail
    ;
    Afifah Shuhada Rosmi
    ;
    Wan Azani Wan Mustafa
    Partial discharge (PD) is one of the most popular failure or breakdown that can happen at high voltage (HV) equipment. PD is the fault that causes the insulation breakdown occurred between two electrodes. It happened or occurred because of the improper insulation, ageing, environment effect and manufacturing defects. The loss of the power will affect consumer and system operation. One of the technique that can measure or detect the PD is by using ultra high frequency (UHF) method for HV equipment insulation condition monitoring and assessment. In this paper, the application of UHF method have been reviewed as the best method to detect PD in transformer, GIS and cable. The UHF method for every electrical equipment is described in order to detect the PD and the laboratory result shows that this method can be considered as suitable technique. Based on this review, the new design in UHF sensor is required in order to improve the sensitivity and bandwidth for PD detection in HV equipment. The valuable parameter such as size and PD frequency range can be used for early stage of designing new the UHF sensor.
  • Publication
    Comparison of Image Restoration using Median, Wiener, and Gaussian Filtering Techniques based on Electrical Tree
    ( 2021-01-01)
    Abdulah C.S.K.
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Baharuddin Ismail
    ;
    Isa M.A.M.
    ;
    Afifah Shuhada Rosmi
    ;
    Wan Azani Wan Mustafa
    Electrical treeing lead to a major cause of a breakdown in solid insulation. Thus reduced solid insulation performance by degrading the insulation. Hence, it is important to study the electrical treeing and learn the root cause of the treeing formation. In this paper, the performances of median, wiener, and gaussian filters in restoring noisy images are studied based on electrical tree images. The electrical tree colour images is being transform into grayscale images, noisy images using impulse noise (salt and pepper), and finally motion blur are applied. Even though, there are several number of filters available, this paper focus on median, wiener, gaussian, and combination of the filters. In the end, comparison between these filters is made to study the efficiency using PSNR, SNR, and MSE in graph form.
  • Publication
    Design of vibration energy harvester for low voltage power supply using finite element methods (FEM) analysis
    ( 2018)
    Afifah Shuhada Rosmi
    The rapid growth of electronic devices miniaturization attract the researchers interest either to save space or for cost reduction. The main purpose of miniaturization is to implement the concept of portable in order to locate the devices everywhere without connected to a power strip. Therefore, the use of battery as a power supply is the only choice to realizing the concepts. However, the improper battery disposal gives the detrimental effects to the environment and human being. Energy harvesting is proposed as the best solution as it provides more comfort and safety to the device compared to the old-fashioned battery. However, the development of lead-free vibration harvester for low frequency of ambient vibration energy is rarely reported. Thus, energy harvester based on zinc oxide (ZnO) piezoelectric material has been chosen as a vibration energy to electrical power transducer as it is compatible with microelectromechanical systems (MEMS) technologies, which can generate power from μW up to mW level power. Powering the devices using energy harvester is really suggested as it can provide clean energy, no need for frequent battery replacement and long-term solution. This research focus on designing and simulating the four different models of micro scale piezoelectric power generator (PPG) cantilever beam type named as PPG 1, PPG 2, PPG 3 and PPG 4 using COMSOL Multiphysics approach. The models with attached proof mass at the end tip were analyses to investigate the capability in converting the ambient vibration energy which is commonly below than 200 Hz and less than 1 g (1 g = 9.81 m/s2) acceleration amplitudes. Two working conditions are considered for the analyses. The first condition is to mount the PPG model to a machinery, while the second condition is to locate the PPG model close to the ambient sound wave energy sources. FEM simulation was done with two types of analysis taken. In order to obtain the required results which are resonant frequency analysis and evaluation of electrical output power, eigenfrequency and frequency domain modules were used. As a result, the frequency resonance for all models is below than 200 Hz. As a highlight of this work, PPG 4 shows the superior capability than other model since able to generate the highest output power which is 17.11 μW when integrated with voltage multiplier. Meanwhile, PPG 2 is more suitable for harvesting low frequency of vibration energy since able to vibrate at lower frequency compared to other models which is as low as 52.77 Hz. Based on these two findings about PPG 2 and PPG 4, PPG 4 is selected as the better model since capable in generating higher output power at resonant frequency less than 200 Hz.
  • Publication
    Hilbert fractal UHF sensor based on partial discharge detection signal for on-line condition monitoring in power transformer
    ( 2020-01-01)
    Roslizan N.D.
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Afifah Shuhada Rosmi
    ;
    Baharuddin Ismail
    ;
    Muzamir Isa
    ;
    Akashah N.A.
    ;
    Mukhtaruddin A.
    PD detection is an effective method of inspecting insulation defects and identifying potential faults in a power transformer. Electromagnetic waves generated due to PD can be detected by ultrahigh-frequency (UHF) sensor in the frequency band greater than 300 MHz. However, the size and the frequency bandwidth of a UHF sensor for PD detection are the concern for practical installation inside a transformer. High sensitivity and wide bandwidth of sensors are needed in order to detect the PD signal in an early stage. This paper presents an array 4th order Hilbert fractal UHF sensor for PD detection inside a power transformer. This UHF sensor was modeled to capture PD signal in a range of frequencies between 300 MHz to 3 GHz. The sensor is designed by using CST software where the transmission lines combined 2 sensors become 1 output by setting the dimension of 100 x 200 mm for length and width with FR4 epoxy substrate of thickness 1.6 mm. Based on the simulation result, the proposed sensor is obtained a PD signal measurement with a reflection coefficient below-10 dB with VSWR ≤5. The advantages of this sensor have a wide bandwidth, high sensitivity and suitable size for easy installation. Thus, this sensor has been qualified as UHF PD detection in the power transformer.
  • Publication
    Electrical Tree Investigation on Solid Insulation for High Voltage Applications
    ( 2021-01-01)
    Abdulah C.S.K.
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Baharuddin Ismail
    ;
    Isa M.A.M.
    ;
    Afifah Shuhada Rosmi
    ;
    Wan Azani Wan Mustafa
    ;
    Kamarol M.
    Electrical treeing is a major cause of a breakdown in solid insulation cable. This phenomenon reduced aging by degrading the insulation, leading to failure in the high voltage materials. The most common experimental set-up in studying the electrical tree is using a needle electrode to initiate the treeing image. Different types of needle and insulation material had been studied from the previous experiment. This paper review the method used to investigate tree growth and its technique to capture the treeing image. Based on this review, several causes delay the treeing process in the needle embedded experiments. In contrast, 2D image processing is the most frequent image developed in the electrical tree on solid insulation.
  • 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.