Khairul Nadiah Khalid
Thumbnail Image
Preferred name
Khairul Nadiah Khalid
Official Name
Khalid, Khairul Nadiah
Alternative Name
Khalid, Khairul Nadiah
Khalid, K. A.
Khalid, K. N.
Main Affiliation
Scopus Author ID
57214973509
Researcher ID
N-6739-2019

Research Output

Filters

3
3
Reset filters

Settings
Now showing 1 - 3 of 3
Thumbnail Image
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.

View
Thumbnail Image
Publication

Modelling of piezoelectric sensor based on ZnO material for partial discharge detection on power transformer

2020-01-01 , Akashah N.A. , Mohamad Nur Khairul Hafizi Rohani , Afifah Shuhada Rosmi , Muzamir Isa , Baharuddin Ismail , Kamarol M. , Roslizan N.D. , Khairul Nadiah Khalid

Detection of partial discharge (PD) in early stages able to reduce the risk of decommissioning of high voltage (HV) equipment. However, the conventional method for PD detection are not suitable for on-site measurement due to electrical disturbance. One of the method in detecting PD signal is piezoelectric based acoustic emission (AE) sensors. In this project, an AE sensor is modelled to obtain a PD signal in the range of 10 – 300 kHz occurred in HV transformer and been found out by simulation and analytical approach. Two models of a piezoelectric sensor with different types of cantilever and different dimension variation starting from 4 mm to 15 mm are designed in the Finite element Method (FEM) in order to investigate the resonant frequency which is matched to the range of AE detection. Zinc oxide (ZnO) as a piezoelectric material is proposed in this project due to its high piezoelectric coupling and environmentally friendly compared to the others material which is harmful. Based on the simulation result, ZnO piezoelectric sensor with the length of 5 mm and thickness of 0.451 mm generates 0.0537 mV electrical potentials under the resonant frequency of 155.30 kHz which is in the range of AE detection technique.

View
Thumbnail Image
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.

View