基于双流卷积神经网络算法的电力光缆监测系统
By using a power optical cable monitoring system based on a dual-stream convolutional neural network algorithm, combined with Φ-OTDR sensing technology, real-time monitoring and fault early warning of highway optical cables have been achieved. This solves the problems of complexity and long response time in existing optical cable management technologies, improves the accuracy of fault location and identification, and provides a unified management platform and backup fiber core management.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- ELECTRIC POWER SCI RES INST OF STATE GRID XINJIANG ELECTRIC POWER CO LTD
- Filing Date
- 2023-10-30
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies make it difficult to achieve real-time monitoring and fault early warning of high-speed optical cables, resulting in complex fault location, long response time, inability to predict damage, chaotic management, lack of unified ledger management, repeated laying of optical cables and chaotic routing information, and inability to grasp the availability of spare fiber cores in real time.
A power optical cable monitoring system based on a dual-stream convolutional neural network algorithm is adopted. Combining Φ-OTDR sensing technology and dual-stream convolutional neural network, the system uses sensing optical fiber and vibration signal acquisition module to classify events using dual-stream convolutional neural network, including spatial flow and temporal flow networks. It also introduces a dual attention mechanism and a spatiotemporal pyramid model to achieve real-time monitoring and fault early warning of the optical cable.
It enables real-time monitoring of highway optical cables, timely detection of potential faults, improved fault location and identification accuracy, reduced response time, provides a unified management platform, ensures the availability of spare fiber cores, and reduces repeated laying of optical cables and confusion in routing information.
Smart Images
Figure CN117451163B_ABST