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RISS 인기검색어
- 검색키워드
- 저자 : Muniraj C. (검색결과 4 건)
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Investigation on Flashover Development Mechanism of Polymeric Insulators by Time Frequency Analysis
Muniraj, C.,Krishnamoorthi, K.,Chandrasekar, S. The Korean Institute of Electrical Engineers 2013 Journal of Electrical Engineering & Technology Vol.8 No.6
This paper deals with the analysis of leakage current characteristics of silicone rubber insulator in order to develop a new condition monitoring tool to identify the flashover of outdoor insulators. In this work, laboratory based pollution performance tests are carried out on silicone rubber insulator under ac voltage at different pollution levels and relative humidity conditions with sodium chloride (NaCl) as a contaminant. Min-Norm spectral analysis is adopted to calculate the higher order harmonics and Signal Noise Ratio (SNR). Choi-Williams Distribution (CWD) function is employed to understand the time frequency characteristics of the leakage current signal. Reported results on silicone rubber insulators show that the flashover development process of outdoor polymer insulators could be identified from the higher order harmonics and signal noise ratio values of leakage current signals.
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Investigation on Flashover Development Mechanism of Polymeric Insulators by Time Frequency Analysis
C. Muniraj,K.Krishnamoorthi,S.Chandrasekar 대한전기학회 2013 Journal of Electrical Engineering & Technology Vol.8 No.6
This paper deals with the analysis of leakage current characteristics of silicone rubber insulator in order to develop a new condition monitoring tool to identify the flashover of outdoor insulators. In this work, laboratory based pollution performance tests are carried out on silicone rubber insulator under ac voltage at different pollution levels and relative humidity conditions with sodium chloride (NaCl) as a contaminant. Min-Norm spectral analysis is adopted to calculate the higher order harmonics and Signal Noise Ratio (SNR). Choi-Williams Distribution (CWD) function is employed to understand the time frequency characteristics of the leakage current signal. Reported results on silicone rubber insulators show that the flashover development process of outdoor polymer insulators could be identified from the higher order harmonics and signal noise ratio values of leakage current signals.
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Jamuna V.,Muniraj C.,Periasamy P. S. 대한전기학회 2023 Journal of Electrical Engineering & Technology Vol.18 No.4
Solar energy generation Photovoltaic modules that work reliably for 20–30 years in environmental conditions can only be cost-effective. The temperature inside the PV cell is not uniform due to an increase in defects in the cells. Monitoring the heat of the PV panel is essential. Therefore, research on photovoltaic modules is necessary. Infrared thermal imaging (IRT) has a significant role in determining the severity of problems in solar panels. Thus, in this work, a maximum power point tracking (MPPT) system based on a new image for thermal imaging is proposed to solve the photovoltaic (PV) defects using linear iterative fault diagnosis method. The thermal camera and new MPPT solution used for fault detection were developed to change the operating point to match the optimized MPP. The simulation work does go through the use of the proposed low-income food-deficient method in the MATLAB environment. The simulation results show the effectiveness of the proposed Linear Iterative Fault Diagnosis (LIFD) method and its ability to detect the fault and track the maximum power of the PV panel. The sensitivity, specificity and accuracy of the proposed work are 98%, 94% and 97%.
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N. Rajasekaran,C. Muniraj,T. Venkatesan,A. Kumaravel 한양대학교 청정에너지연구소 2024 Journal of Ceramic Processing Research Vol.25 No.1
Nanocomposites (LDPE + BaTiO3 ceramic) with different volume ratio of 0%, 1%, 3% and 5% were prepared by melt mixingmethod. Scanning Electron microscopy (SEM) results for nanocomposites materials shows that the nanofiller particle disperseduniformly throughout the entire surface and there is no agglomeration of nanoparticles. BaTiO3 ceramic nanoparticle structureand crystallite size were investigated using X-ray diffraction (XRD) studies. Using energy-dispersive X-ray spectroscopy (EDS),the chemical composition of the composite material has been determined. EDS can have determined the types of elementspresent in the sample and their relative concentrations. To assess the behavior of nanocomposites, experimental test wasconducted to predict the electrical parameters such as dielectric breakdown strength, DC volume resistivity, dielectric constantand Dissipation factor. The dielectric strength was estimated using a feed forward neural network (FFNN) and ArtificialNeural Network and Fuzzy Inference system (ANFIS) technique under various conditions and filler percentages. From the testresults, it was observed that nanocomposites with 3% wt has the highest dielectric strength. In Weibull analysis, feed forwardneural network (FFNN) and Artificial Neural Network and Fuzzy Inference system (ANFIS) predicted that with the inclusionof nanofiller, the electrical breakdown strength of nanocomposite materials was increased. The results show that, dielectricpermittivity and dissipation factor (tan delta) of the nanocomposites materials decreased and increased correspondingly withincrease in frequency. Further increase in mixing proportion of nanocomposites, it was found that the inter particle distanceis decreased due to that the mobility of charge carrier is increased and the material loses its dielectric property. From theexperimental test results, it was found that LDPE/BaTiO3 ceramic filler nanocomposites materials with 3% wt have betterelectrical properties compared to neat LDPE.
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