Power distribution equipment intelligent fault early warning method and system based on internet of things

CN121808283BActive Publication Date: 2026-06-19CHINA CONSTRUCTION INDUSTRIAL & ENERGY ENGINEERING GROUP CO LTD

Patent Information

Authority / Receiving Office: CN · China
Patent Type: Patents(China)
Current Assignee / Owner: CHINA CONSTRUCTION INDUSTRIAL & ENERGY ENGINEERING GROUP CO LTD
Filing Date: 2026-03-09
Publication Date: 2026-06-19

AI Technical Summary

Technical Problem

Existing early warning level management technologies lack flexibility and foresight, and cannot intelligently identify the spatiotemporal correlation and recurrence characteristics of equipment failures. This results in a large number of low-value alarms interfering with normal operation and maintenance or delaying early warning of major failure risks, failing to meet the needs of modern intelligent operation and maintenance.

Method used

By collecting time-series operation data of power distribution equipment, cleaning and aligning it, analyzing comprehensive characteristics based on sliding time windows, and combining threshold, statistical anomaly and trend analysis, a comprehensive evidence set is generated and processed in parallel. Using cooling period and suppression threshold judgment, accurate early warning level confirmation and historical alarm sequence update are achieved.

Benefits of technology

It enables early identification and accurate response to power distribution equipment faults, reduces false alarms and alarm storms, improves operation and maintenance efficiency and the accuracy and timeliness of fault early warning, and ensures the efficient use of operation and maintenance resources.

✦ Generated by Eureka AI based on patent content.

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Patent Text Reader

Abstract

This invention discloses an intelligent fault early warning method and system for power distribution equipment based on the Internet of Things (IoT), belonging to the field of power distribution equipment fault early warning technology. The invention collects time-series operational data of the power distribution equipment, cleans and aligns it, and analyzes the comprehensive characteristics of the power distribution equipment based on a sliding time window. Based on these comprehensive characteristics, it analyzes abnormal situations of the power distribution equipment; it confirms the initial fault level based on the abnormal situations; when a new fault event occurs in the power distribution equipment, it analyzes the upgrade risk assessment value of the power distribution equipment based on the corresponding historical alarm event sequence; based on the upgrade risk assessment value, it confirms the final early warning level of the new fault event of the power distribution equipment; and it updates the historical alarm event sequence. This reduces the risk of alarm storms and improves operation and maintenance efficiency.

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