Khairul Nadiah Khalid
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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

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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.

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Analysis of acoustic sensor placement for PD location in power transformer

2020 , Khairul Nadiah Khalid , Rohani, Muhammad Nur Khairul Hafizi , Chai Chang YII , Baharuddin Ismail , Muzamir Isa , Wan Nurul Auni Wan Muhammad

Partial discharge (PD) is an abnormal activity that occurs in high-voltage components, such as power cables, switchgear, machines, and power transformers. Such activity needs to be diagnosed for the equipment to last longer as PD could harm the insulation and potentially lead to asset destruction from time to time. Moving one or more externally mounted acoustic sensors to different locations on the transformer tank is commonly used in order to detect and locate PD signal occurring in the power transformer. However, this procedure may lead to less accuracy in PD identification. Therefore, this research paper presents an analysis of acoustic sensor placement based on time of arrival (TOA) technique for PD location in a power transformer. The detection and location can be determined by permanently installing the acoustic sensor to provide valuable data in an early stage of occurrence for online condition PD monitoring. Several methods are available for the detection of PD signal, whereby one of the best choices is via acoustic emission (AE). PD creates an ultrasonic signal used for PD detection. This paper proposes the possible placement of AE sensors to be mounted on the power transformer wall based on ideal and static PD signals. The sensors were placed in order to capture the PD signal without any disturbance signal from inside or outside the tank. The time for the signal for the first approach for each sensor is recorded to estimate the PD location using the TOA technique. A comparison between the least square method (LSM) and Gauss-Jordan elimination (GJE) for the TOA technique was analyzed to differentiate the resulting performance. This research utilized three different PD sources to apply the performance analysis on PD locations, while five cases were proposed to represent the five different placements of four sensors for the analysis. This research ultimately suggests that sensors be placed and randomly mounted on the four sides of the transformer tank, with one sensor allocated to one side. Among all five cases, Case 1 and Case 5 yielded a displacement error (DE) less than others, while between these two cases, Case 5 gave the lowest DE. The findings were recorded based on LSM and GJE methods used to differentiate the resulting performance.

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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.

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