Grounding wire state monitoring and early warning system and method based on random forest algorithm

By combining multi-source sensor networks with random forest algorithms, a grounding wire status monitoring and early warning system with a hierarchical decision tree structure is constructed. This solves the problems of low efficiency and poor data continuity in existing technologies, and realizes high-precision early warning and predictive maintenance of grounding wire status, thereby improving the accuracy of composite fault identification and the reliability of on-site early warning.

CN121461601BActive Publication Date: 2026-06-26SICHUAN WESTERN ENERGY CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
SICHUAN WESTERN ENERGY CO LTD
Filing Date
2025-11-10
Publication Date
2026-06-26

AI Technical Summary

Technical Problem

Existing grounding wire monitoring schemes suffer from problems such as low efficiency, poor data continuity, and inaccurate early warning judgments. In particular, they are difficult to achieve multi-dimensional information fusion and adaptive capabilities in complex electromagnetic environments, resulting in high false alarm rates, frequent missed alarms, and insufficient communication reliability.

Method used

A multi-source sensor network is used to collect multi-dimensional operational data. A grounding wire status monitoring and early warning system with a hierarchical decision tree structure is constructed using the random forest algorithm. Dynamic feature weight adjustment is achieved by combining feature importance analysis. The system outputs grounding wire fault probability assessment and fault cause analysis, and provides information to the field using a hierarchical differentiated early warning method.

Benefits of technology

It improves the accuracy and reliability of grounding wire operation status monitoring, enhances the robustness of the model in strong electromagnetic interference environments, realizes intelligent data acquisition and early warning decision-making throughout the entire process, and improves the accuracy of fault identification and the reliability of on-site information transmission.

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Abstract

The application provides a grounding wire state monitoring and early warning system and method based on a random forest algorithm, relates to the technical field of power safety monitoring, and solves the problems of low efficiency, poor data continuity, inaccurate early warning judgment and other limitations in the prior art. In the system, a multi-source sensor network collects multi-dimensional operation data corresponding to the grounding wire and transmits the data to a data acquisition terminal; the data acquisition terminal performs feature extraction processing, generates a feature vector set, and uploads the feature vector set to a cloud data processing platform; the cloud data processing platform uses a random forest classification model, based on the feature vector set, adjusts the dynamic feature weight through feature importance analysis, constructs a hierarchical decision tree structure, identifies and outputs the grounding wire fault mode, and issues the grounding wire fault mode to a local early warning terminal; the local early warning terminal adopts a hierarchical differentiated early warning mode and provides early warning information to the grounding wire site. The application effectively realizes high-precision early warning and predictive maintenance of the grounding wire state.
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