High Voltage Insulation Surface Condition Analysis Using Time Frequency Distributions
In high voltage engineering, insulation is the most important part to prevent the flow of current to undesired paths. Currently, polymeric type of insulation is widely used because of its advantages which are light, easy to fabricate, and have good dielectric properties compared to traditional ceram...
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my.utem.eprints.162122022-02-21T11:34:13Z http://eprints.utem.edu.my/id/eprint/16212/ High Voltage Insulation Surface Condition Analysis Using Time Frequency Distributions Nurbahirah, Norddin T Technology (General) TK Electrical engineering. Electronics Nuclear engineering In high voltage engineering, insulation is the most important part to prevent the flow of current to undesired paths. Currently, polymeric type of insulation is widely used because of its advantages which are light, easy to fabricate, and have good dielectric properties compared to traditional ceramic or non polymeric insulation. In previous researches, leakage current frequency component is mainly used to analyze surface condition of polymeric insulation and it is, normally, analyzed by using fast Fourier transform (FFT). However, the technique only presents spectral information and is not suitable for the leakage current signal that consists of magnitude and frequency variations. Thus, time-frequency analysis technique needs to be employed to provide spectral and temporal information of the signal. This research presents the analysis of leakage current using time-frequency distributions (TFDs). Time-frequency distributions (TFDs) such as spectrogram and S-transform are applied to represent the leakage current (LC) in time-frequency representation (TFR). These techniques extract relevant information from TFR include root mean square current (RMS), total harmonic distortion (THD), total non harmonic distortion (TnHD) and total current waveform distortion (TWD). Tracking and erosion test via Incline Plane Test complying with BS EN60587-2007 is conducted to collect different leakage current patterns on polymeric and non polymeric material. Furthermore, the performance of the TFDs is evaluated based on their TFRs accuracy and the results shows that S-transform outperforms spectrogram in term of frequency and time resolution. Thus, the classification of leakage current using parameters from S-transform can be implemented to determine material state and severity instantaneously. 2014 Thesis NonPeerReviewed text en http://eprints.utem.edu.my/id/eprint/16212/1/High%20Voltage%20Insulation%20Surface%20Condition%20Analysis%20Using%20Time%20Frequency%20Distributions%2024%20Pages.pdf text en http://eprints.utem.edu.my/id/eprint/16212/2/High%20Voltage%20Insulation%20Surface%20Condition%20Analysis%20Using%20Time%20Frequency%20Distributions.pdf Nurbahirah, Norddin (2014) High Voltage Insulation Surface Condition Analysis Using Time Frequency Distributions. Masters thesis, Universiti Teknikal Malaysia Melaka. http://library.utem.edu.my:8000/elmu/index.jsp?module=webopac-d&action=fullDisplayRetriever.jsp&szMaterialNo=0000091000 |
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In high voltage engineering, insulation is the most important part to prevent the flow of current to undesired paths. Currently, polymeric type of insulation is widely used because of its advantages which are light, easy to fabricate, and have good dielectric properties compared to traditional ceramic or non polymeric insulation. In previous researches, leakage current frequency component is mainly used to analyze surface condition of polymeric insulation and it is, normally, analyzed by using fast Fourier transform (FFT). However, the technique only presents spectral information and is not suitable for the leakage current signal that consists of magnitude and frequency variations. Thus, time-frequency analysis technique needs to be employed to provide spectral and temporal information of the signal. This research presents the analysis of leakage current using time-frequency distributions (TFDs). Time-frequency distributions (TFDs) such as spectrogram and S-transform are applied to represent the leakage current (LC) in time-frequency representation (TFR). These techniques extract relevant information from TFR include root mean square current (RMS), total harmonic distortion (THD), total non harmonic distortion (TnHD) and total current waveform distortion (TWD). Tracking and erosion test via Incline Plane Test complying with BS EN60587-2007 is conducted to collect different leakage current patterns on polymeric and non polymeric material. Furthermore, the performance of the TFDs is evaluated based on their TFRs accuracy and the results shows that S-transform outperforms spectrogram in term of frequency and time resolution. Thus, the classification of leakage current using parameters from S-transform can be implemented to determine material state and severity instantaneously. |
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Thesis |
author |
Nurbahirah, Norddin |
author_facet |
Nurbahirah, Norddin |
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Nurbahirah, Norddin |
title |
High Voltage Insulation Surface Condition Analysis Using Time Frequency Distributions |
title_short |
High Voltage Insulation Surface Condition Analysis Using Time Frequency Distributions |
title_full |
High Voltage Insulation Surface Condition Analysis Using Time Frequency Distributions |
title_fullStr |
High Voltage Insulation Surface Condition Analysis Using Time Frequency Distributions |
title_full_unstemmed |
High Voltage Insulation Surface Condition Analysis Using Time Frequency Distributions |
title_sort |
high voltage insulation surface condition analysis using time frequency distributions |
publishDate |
2014 |
url |
http://eprints.utem.edu.my/id/eprint/16212/1/High%20Voltage%20Insulation%20Surface%20Condition%20Analysis%20Using%20Time%20Frequency%20Distributions%2024%20Pages.pdf http://eprints.utem.edu.my/id/eprint/16212/2/High%20Voltage%20Insulation%20Surface%20Condition%20Analysis%20Using%20Time%20Frequency%20Distributions.pdf http://eprints.utem.edu.my/id/eprint/16212/ http://library.utem.edu.my:8000/elmu/index.jsp?module=webopac-d&action=fullDisplayRetriever.jsp&szMaterialNo=0000091000 |
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1725976095309692928 |
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13.211869 |