Zinc oxide arrester insulation degradation trend analysis method

Abstract

The invention relates to a zinc oxide arrester insulation degradation trend analysis method. The zinc oxide arrester insulation degradation trend analysis method comprises the steps of: acquiring lightning arrester online monitoring data, basic standing book data and temperature and humidity data; performing data cleaning on the acquired data; then, subjecting the cleaned data to denoising processing by means of mathematical morphology, so as to effectively eliminate signal noise while reserving global and local characteristics of an original signal, and improve the online monitoring data reliability; performing EMD analysis to extract each modal component in the data signal and representing a central trend component of the data original signal, acquiring each inflection point of a curve from the central trend component, further determining a data variation trend between the adjacent inflection points according to data variation rate warning upper and lower limits and the data variation rate between the adjacent inflection points, and combining the variation trend of the adjacent inflection points to obtain a lightning arrester monitoring data variation trend, and sending out insulation degradation trend warning according to a lighting arrester insulation degradation warning factor. The zinc oxide arrester insulation degradation trend analysis method realizes the efficient perception of an insulation fault of the lightning arrester and guarantees the safe and reliable operation of a power grid.

Description

technical field [0001] The invention relates to the technical field of electric power safety, in particular to a method for analyzing the insulation deterioration trend of a zinc oxide arrester. Background technique [0002] Zinc oxide arrester is an important protection device for limiting overvoltage in the power grid. It can provide a certain protection margin for important electrical equipment. The reliability of its operation is related to the stable operation of the power grid, but the arrester has been subjected to system voltage, overvoltage, pollution , internal damp and other factors, the insulation performance will gradually deteriorate, which may lead to equipment failure, affecting the safety and stability of the power system and the reliability of power supply. Influenced by factors such as the operating environment, data volatility is large, and it is difficult to judge the trend of monitoring data changes. Currently, the processing and analysis of online moni...

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Problems solved by technology

[0002] Zinc oxide arrester is an important protection device for limiting overvoltage in the power grid. It can provide a certain protection margin for important electrical equipment. The reliability of its operation is related to the stable operation of the power grid, but the arrester has been subjected to system voltage, overvoltage, pollution , internal damp and other factors, the insulation performance will gradually deteriorate, which may lead to equipment failure, affecting the safety and stability of the power system and the reliability of power supply. Influenced by factors such as the operating environment, data volatility is large, and it is difficult to judge the trend of monitoring data changes. Currently, the processing and analysis of online monitoring data is relatively mature, and the accumulated mass can be fully utilized. Big data processing framework, mathematical morphology filtering, and EMD algorithm can be applied , effectively carry out the analysis of the deterioration trend of the arrester insulation, realize the rapid perception of the change trend of the arrester insulation, and on this basis, the power supply reliability of the power grid equipment has become very urgent

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