基于智能融合终端的数据传输链路异常检测方法及系统
By constructing extreme sample sequences and dynamic threshold models in intelligent fusion terminals and combining them with line loss rate verification, the reliability and accuracy issues of abnormal detection in the data transmission link between transformers and meters were resolved. This enabled adaptation to complex operating conditions and accurate detection, thereby improving the stability of the power grid and its fault early warning capabilities.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- WUXI HENGTONG ELECTRIC CO LTD
- Filing Date
- 2026-04-30
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies are insufficient to effectively distinguish between abnormal data transmission links between transformers and meters in smart converged terminals, resulting in inadequate reliability and accuracy in data distortion detection, which fails to meet the refined operation and maintenance needs of smart grids.
By acquiring transformer and meter current data under normal operating conditions from intelligent fusion terminals, an extreme sample sequence is constructed, sample density analysis is performed, current levels are adaptively classified, dynamic thresholds are calculated, a hierarchical judgment model is constructed for anomaly detection, and line loss rate is used for auxiliary verification to achieve accurate detection of data transmission links.
It significantly improves the adaptability and accuracy of data transmission link anomaly detection, effectively identifies complex anomaly scenarios, and enhances the reliability of power grid operation and the timeliness of fault early warning.
Smart Images
Figure CN122133035B_ABST