研究目的
To classify the contamination level of glass insulators used in high voltage transmission lines using a statistical approach based on radio frequency signals.
研究成果
The statistical method using mean and standard deviation effectively discriminates between clean and polluted glass insulators in the 30 MHz to 130 MHz range with horizontal polarization, unaffected by voltage levels. Filtering can mitigate environmental interference, and the approach is applicable for fault detection in power systems.
研究不足
Environmental interferences (e.g., FM radio and TV signals) can affect results and require filtering; the method may not work well at higher frequencies or with vertical polarization; a larger database is needed for different types of pollution and defects.
1：Experimental Design and Method Selection:
The experiment was designed to measure RF signals emitted by glass insulators under high voltage using statistical methods (mean and standard deviation) for classification.
2：Sample Selection and Data Sources:
Two types of glass insulators (clean and polluted) were used, collected from a 69 kV power line in Brazil. Each was tested at three voltage levels (8 kV, 12 kV, 15 kV rms).
3：List of Experimental Equipment and Materials:
Spectrum analyzer, log-periodic antennas (two types covering 30 MHz to 300 MHz and 300 MHz to 1 GHz), high voltage control desk, and glass insulators (model ST-254 V8 CB).
4：Experimental Procedures and Operational Workflow:
Insulators were placed in a high voltage laboratory; RF signals were captured using antennas connected to a spectrum analyzer, with measurements taken in frequency bands from 30 MHz to 1 GHz using horizontal and vertical polarizations. Data was collected with 2000 samples per 100 MHz bandwidth, with 50 MHz overlap.
5：Data Analysis Methods:
Mean and standard deviation were computed for each bandwidth using a spreadsheet, and results were plotted to classify insulator conditions.
独家科研数据包，助您复现前沿成果，加速创新突破
获取完整内容
