Live detection method for lightning arrester

By analyzing the detection types and factors of the lightning arrester, the optimal detection type and preferred detection data are determined, and a predictive detection model is constructed, the existing lightning arrester detection methods are solved, and higher detection accuracy and lower detection costs are achieved.

CN119716294AActive Publication Date: 2025-03-28HUANENG BUTUO WIND POWER GENERATION CO LTD
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Patent Information

Application Number
CN202411502621.X
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-10-25
Publication Date
2025-03-28
Estimated Expiration
2044-10-25

AI Technical Summary

Technical Problem

The existing live detection methods for lightning arresters have problems such as low measurement accuracy, long detection time or high detection cost.

Method used

By analyzing the characteristic detection data and feature factors of each detection type, the detection quality evaluation results of the characteristic detection data are determined, the optimal detection type and preferred detection data are obtained, and a predictive detection model is constructed to improve detection accuracy, reduce detection costs, and the interference of the surrounding environment to detection.

Benefits of technology

It improves the detection accuracy of the lightning arrester status, reduces detection costs, reduces the interference of the surrounding environment to detection, and improves the operation reliability of the lightning arrester.

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Abstract

The invention discloses a lightning arrester live-line detection method, which comprises the following steps: acquiring a historical detection log of lightning arrester live-line detection and historical detection data in the historical detection log, and preprocessing the historical detection data to obtain initial detection data; classifying the initial detection data according to the detection types, and extracting feature detection data in different historical detection logs of each detection type and feature factors of the feature detection data; performing detection quality evaluation on the characteristic factors, and determining an optimal detection type and optimal detection data according to a detection quality evaluation result; constructing a prediction detection model, obtaining real-time detection data according to the optimal detection type, and inputting the real-time detection data into the prediction detection model to obtain a prediction detection result; the reliability of the prediction detection result is calculated, the detection precision is improved, the detection cost and the interference of the surrounding environment on the detection are reduced, the detection accuracy of the state of the lightning arrester is ensured, and the operation reliability of the lightning arrester is improved.
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