Lightning arrester fault positioning method
Through the combination of multi-sensors and AI models, accurate points and intelligent maintenance of lightning arrester failures are achieved, and the problems of low misjudgment and positioning accuracy in the existing technology are solved, and the service life of the lightning arrester is extended.
CN120405338APending Publication Date: 2025-08-01FUJIAN POLYTECHNIC OF WATER CONSERVANCY & ELECTRIC POWER
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Patent Information
- Application Number
- CN202510405084.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-01
- Publication Date
- 2025-08-01
AI Technical Summary
Technical Problem
The existing lightning arrester fault fixed-point method is difficult to distinguish equipment aging from potential faults, there is a risk of misjudgment or misjudgment, and the positioning accuracy is low.
Method used
Multi-sensor monitoring lightning arrester is used, combined with the Internet of Things and AI models for real-time monitoring and analysis, and automatically classifies health status through the support vector machine model, uses the traveling wave method to calculate the fault location and correct errors, and intelligently adjust the maintenance cycle.
Benefits of technology
Effectively distinguish between minor faults and aging, improves fault positioning accuracy, and extends the service life of the lightning arrester.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention discloses a lightning arrester fault positioning method, which comprises the following steps of S1, installing an intelligent monitoring terminal externally connected with multiple sensors near a lightning arrester, monitoring the lightning arrester by adopting the multiple sensors, and preprocessing monitored data; s2, transmitting the monitoring data to a power operation and maintenance center by using the Internet of Things (IoT) to realize remote real-time monitoring; and S3, comparing long-term monitoring data with a normal lightning arrester database, and analyzing whether an abnormal trend exists or not. According to the invention, the fault condition of the lightning arrester is analyzed by combining the data monitored by multi-sensor fusion and adopting an intelligent analysis method, the problem that a slight fault and aging are difficult to distinguish is effectively solved, the fault position is corrected through the AI model, the fault positioning precision is improved, and the fault positioning accuracy is improved. In addition, the service life of the lightning arrester can be effectively prolonged in cooperation with the mode of intelligently adjusting the maintenance period through the AI prediction model, and the use requirement is met.
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