Mohamad Nur Khairul Hafizi Rohani

Partial Discharge (PD) is a critical indicator of electrical insulation degradation that can lead to the failure of high-voltage equipment such as power transformers. This study investigates the sensitivity of PZT-5H and low-cost piezoelectric sensors in detecting acoustic signals emitted by PD activity. PD generates acoustic waves due to voids within insulation; however, conventional monitoring methods are costly and often require system shutdowns. Thus, non-invasive PD monitoring is essential for reducing maintenance costs and improving system reliability. The proposed PZT-5H sensor demonstrated strong potential in capturing acoustic emissions from PD events, particularly within insulating oil. In contrast, low-cost piezoelectric sensors exhibited lower sensitivity. Nevertheless, PZT-5H sensors show promise as effective tools for non-invasive PD detection, supporting broader adoption of this technique. This study highlights the feasibility of piezoelectric sensors, especially PZT-5H, in extending the operational life and reliability of power transformers through early PD detection.

Typically, busbars are used to transmit and distribute currents in a bus duct system. The alarming use of nonlinear loads in the industrial sector or at residentials, such as arc welding, computers, ballast lighting, variable speed drives, and so on, has resulted in the generation of harmonics in current distortion, which are uncontrolled and thus increase heat generation within the system. The research conducted in this paper focuses on the prediction of the heat distribution as well as the analysis on operating temperature of a single busbar with compliance to the British National and International Standard (BS 159: 2014) using the Finite Element Method (FEM) in COMSOL Multiphysics software. The copper busbar dimension used for this research was 20mm x 6mm x 300mm, and the fundamental Root Mean Square (RMS) current was 419.1 A. The size of this busbars can withstand the maximum current of 430 A at a maximum operating temperature of 90°C, which complies with the standard requirement. The fundamental current is injected with variation of total harmonic distortion in current up to 55% with an interval of 5%. According to the findings, the operating temperature increases in direct proportion to the increase in total harmonic distortion with the current injections. With the presence of 55% of total harmonics in the current, the current was increased up to 57.73 A from the fundamental current, while the operating temperature was increased up to 140C from the fundamental temperature. The total harmonics in current produced by the nonlinear loads could affect the operating temperature of the busbars, and this continuous operation of current flow will affect the busbars' lifespan due to the occurrence of overheating.

Electrical treeing occurred in solid dielectric materials, especially in electrical application with high voltage. The occurrence of electrical tree happens when high electric fields applied, causing tiny channels or paths to form. The main issue during the data collection process is the changes of lighting, making it difficult to study the tree's propagation length, fractal dimension, and growth rate due to corrupted images. This research aims to analyse electrical tree structure images in XLPE material using a CCD camera and develop image de-noising techniques to suppress noise on the electrical tree image. The performance was then analysed using the Otsu thresholding algorithm for accurate segmentation. The methodology was divided into four phases: sample preparation, experimental setup, image pre-processing in MATLAB, and testing four de-noising filters: Wiener, median, NLM, and Gaussian. The Wiener filter with higher PSNR, SNR, and RMSE was selected and using superimposed method, both threshold wavelet transforms and wiener was combined to eliminate the noise. Finally, the proposed method of superimposed was tested with the Otsu thresholding method to evaluate accuracy, sensitivity, and specificity of the combination filter. Based on the analysis of PSNR, SNR, and RMSE, the performance of the threshold wavelet and Wiener filter (TWWF) de-noising technique improves the image quality of the electrical tree structure. Thus, for the Otsu thresholding segmentation algorithm analysis, it also had the highest values in terms of accuracy, sensitivity, and specificity.

Electrical treeing is a common problem during the pre-breakdown phenomenon in solid insulations due to the damage caused by Partial Discharge (PD) that progresses through stressed insulation via chemical degradation, which resembles the shape of a tree root. This resulted in a decrease in performance through degrading the insulation, which became a serious problem while dealing with electrical equipment. Hence, a deep understanding of electrical tree structure is vital to improving the quality of solid insulations. Ergo, optical microscopy is primarily used to examine tree structures, shapes, and fractal dimensions to reconstruct electrical tree structures for morphological study. However, optical microscopy images are frequently degraded by noise from readout procedures or image data acquisition systems, noise caused by occlusion, illumination, non-uniform intensity, destroying potential tree pixels, and a critical loss of information about the electrical tree structures. Therefore, this research proposed the Wiener Median Fusion (WMF) filter for electrical tree study. The performance of the WMF de-noising technique improves the image quality for the precise portrayal of the electrical tree structure based on thresholding segmentation algorithm analysis in terms of accuracy, sensitivity, and false positive rate. Based on the analysis of the thresholding segmentation algorithm, Otsu's thresholding exhibits the highest result compared to Niblack. The Otsu's overall percentage in terms of accuracy is 80.2934%, the sensitivity is 99.1513%, and the false positive rate is 82.6265%.

Partial discharges (PD) are small electrical discharges that occur within insulation materials and can lead to equipment failure and safety hazards. The Ultra High Frequency (UHF) sensor consists of a broadband antenna and a UHF receiver, which are designed to detect and analyse the electromagnetic emissions from partial discharges. This paper presents the design and characterization of the 4th order Hilbert fractal UHF sensor for PD detection in power transformer. The sensor is designed to operate in the frequency range of 300 MHz to 3 GHz and is optimized for high gain and directivity. The performance of the sensor is evaluated using simulation and measurement techniques. Simulation results show that the sensor has directivity of 7.9 dBi and reflection coefficient below -10 dB with VSWR ≤ 5.

This research evaluates the performance of edge-based segmentation methods in analysing two-dimensional (2D) electrical tree images obtained during high-voltage (HV) electrical tree experiments. Non-uniform illumination in 2D optical images poses challenges in accurately extracting and measuring the original treeing image. Edge segmentation emerges as a promising solution to precisely distinguish tree structures from the insulation background within the image. Cross-linked polyethylene (XLPE) samples were subjected to HV stress for real-time propagation observation, followed by extraction and segmentation of treeing images using edge-based operators. The findings emphasize the superiority of the Roberts edge operator in accurately detecting electrical trees, showcasing the highest average accuracy of 97.01% and 99.58% specificity, while also demonstrating relatively high sensitivity. Moreover, the Roberts method provide much precisely measures the propagation length and width than conventional measurement method, closely approximating the actual tree measurements. This research emphasizes the significance of accurate segmentation for investigating electrical tree propagation in XLPE materials and provides recommendations for future research, especially in HV XLPE cable manufacturing.

Nowadays, every single distribution system needs to install an appropriate relay to keep the system safe. The operational and commonly recommended relay for distribution systems is the overcurrent (OC) relay. Throughout the distribution system, the protective relay is one of the methods that can detect and protect the location according to its observation from any fault from abnormal activity. Note that time coordination between the protective equipment relay needs to be a minimum of time interruption to prevent faults occurs. The ideal setting for all coordination protection relays is necessary to protect the device against electrical failure and interference. This paper analyzes the real results data collected for the selected commercial building of an OC relay implemented in a distribution board for high voltage and low voltage downward at a commercial building. All the parameters need to be clarified first before testing has been made and measurement is carried out using the MICROTEST 860 set. Based on the analysis, it proves that according to the IEC Standard of 0.10-time multiplier Setting (TMS) is practical to be used to obtain the operation time in seconds for the current curve set. Other than that, the results show that the normal inverse curve from manual calculation results is more accurate compared to the service setting (SS) made based on the incoming setting in a real commercial building. The case study for OC relay setting is related between current injection and time-tripping, which complies with the IEC 60255-3 standard using its formula. This method was applied to determine the characteristics of the curve. Hence, this research successfully determined the proper methods for the OC relay setting for the power distribution system. Besides, the feasibility and efficiency of OC relay data transmission are tested and checked successfully to implement the measurement method in the relay coordination study.

Slow-moving product is harmful to the business. The slow-moving products take up space and tie up the company’s capital and leave the company with fewer funds to invest in its business. Several factors can cause this issue. There are several methods ranging from statistics to heuristic methods for a company to identify slow-moving inventory but all of them rely on data. In this paper, a partitioning technique from the graph network is proposed to partition the inventories or products into a few clusters. It can help the company to identify what group does the product belongs to and at the same time suggest to the company which product can be paired up or bundled up together to clear up aging and slow-moving products. The partition technique is proposed, and the algorithm is coded using the Visual C++ programming language. The simulation results show that the proposed method can partition the task graph onto smaller subgraphs. The subgraphs called cluster consists of the nodes or products with similar purchase volume (the strong connection between the two nodes). Implementing the partitioning technique could help the companies or managers select the appropriate product to be paired together when doing the promotion.

The Electroluminescence (EL) technique has garnered significant interest over time for its reliable outcomes that enrich our understanding of the onset of electrical degradation in polymeric material. There is growing interest in combining both the EL technique and space charge measurement methods to obtain a more profound knowledge of the degradation and ageing of insulation. The generation of charge carriers in polymeric materials is widely acknowledged to be a crucial aspect of EL, involving injection, de-trapping, and field dissociation processes. This research investigates the variables that influence how EL emissions behave, including applied voltage or electric field, applied electrical frequency, ageing of material, and selection of materials and gases employed. It was found that these factors can be helpful in predicting the process of electrical ageing in insulation to avoid any catastrophes that may occur. A mathematical approach relating these factors and the intensity of EL is proposed through the aid of Dimensional Analysis method. A close relationship is obtained that suggests this mathematical approach can be utilised as a tool to predict electrical ageing of insulation material.

This paper reviews several studies of image de-noising on digital image processing and applications. Noisy images contain different noise that exist either due to environment or electronic interferences. Ergo, de-noising is crucial to eliminate the noise that disturb data collecting process. The impact of de-noising on image processing can result for accurate and precise data collected from the image. Additionally, de-noising process required several crucial steps that help to enhance knowledge on digital image and its application. Hence, study and understanding de-noising can improve multiple aspect such as image quality, data sensitivity and specificity, accuracy of the collected data, and increase the percentage of each parameter.