CN-122027648-A - Electric power communication network intelligent collaborative management system based on multi-mode sensing and knowledge graph driving and working method thereof

CN122027648ACN 122027648 ACN122027648 ACN 122027648ACN-122027648-A

Abstract

The invention discloses an intelligent collaborative management system of an electric power communication network based on multi-mode sensing and knowledge graph driving and a working method thereof, and belongs to the technical field of intelligent operation and maintenance of the electric power communication network. The method and the system comprise an intelligent line arrangement module, a network dynamic modeling module, a multidimensional service collaborative scheduling module, an equipment intelligent monitoring and maintaining module, an overhaul conflict intelligent identification module, an optical transmission path self-adaptive optimization module and a central intelligent decision platform. The invention realizes the whole-flow closed-loop management from line physical arrangement, network topology modeling, service dynamic scheduling, equipment state monitoring, overhaul conflict early warning to optical transmission path optimization through multi-mode data fusion and knowledge map construction, and improves the operation reliability, resource utilization efficiency and intelligent operation and maintenance level of the power communication network.

Inventors

LIN BINGHUA
LIN QINGCAI
LIU XIANBIN
XIE XINYU
CHEN GAIGUO
LIN FENGJIAO
RUAN XIJIANG
PAN JINCHAO
CHEN JINSHAN
LIN LIFEN
LIN LIPING
TU LINFENG

Assignees

国网福建省电力有限公司三明供电公司
国网福建省电力有限公司

Dates

Publication Date: 20260512
Application Date: 20260130

Claims (9)

1. An intelligent collaborative management system of an electric power communication network based on multi-mode perception and knowledge graph driving is characterized by comprising: the intelligent circuit arrangement module is used for automatically cleaning and uniformly winding the cables in the power communication relocation process; The network dynamic modeling module is used for constructing a knowledge graph of the power communication equipment and dynamically reflecting the association degree and influence among the equipment; The multidimensional service collaborative scheduling module is used for carrying out resource collaborative mapping and scheduling based on service priority and region characteristics; the intelligent equipment monitoring and maintaining module is used for realizing equipment classification monitoring, predictive maintenance and operation and maintenance plan dynamic matching; the overhaul conflict intelligent recognition module is used for automatically recognizing time, resource and logic conflict based on the knowledge graph and the attention mechanism; The self-adaptive optimization module of the optical transmission path is used for monitoring the fluctuation of the link quality in real time and dynamically adjusting the transmission path through reinforcement learning; the central intelligent decision platform is used for integrating the modules to realize multi-source data fusion, situation awareness and cooperative control.
2. The intelligent collaborative management system for the power communication network based on the multi-mode sensing and the knowledge-graph driving according to claim 1, wherein the intelligent circuit arrangement module comprises a cleaning mechanism, a reciprocating sliding positioning mechanism and a coiling mechanism, and supports synchronous cleaning and uniform arrangement of cables in the coiling process.
3. The intelligent collaborative management system for the power communication network based on the multi-mode sensing and the knowledge graph driving according to claim 1, wherein the network dynamic modeling module dynamically adjusts the node mapping area and the edge structure length based on the equipment operation data and visually reflects the equipment state and the association strength.
4. The intelligent collaborative management system for the power communication network based on the multi-mode sensing and the knowledge graph driving according to claim 1, wherein the multi-dimensional business collaborative scheduling module supports differentiated bearing of control type business and non-control type business and performs resource mapping based on a regional scheduling rule table.
5. The intelligent collaborative management system for the power communication network based on the multi-mode sensing and the knowledge graph driving according to claim 1, wherein the intelligent monitoring and maintenance module of the equipment divides the equipment into one class, two classes and three classes and implements a differential monitoring strategy based on fault history and operation parameters.
6. The intelligent collaborative management system of the power communication network based on multi-mode sensing and knowledge graph driving according to claim 1, wherein the intelligent maintenance conflict identification module optimizes the knowledge graph by adopting a multi-head attention mechanism, so as to improve the conflict identification efficiency and accuracy.
7. The intelligent collaborative management system for the power communication network based on the multi-mode sensing and the knowledge graph driving according to claim 1, wherein the adaptive optimization module for the optical transmission path dynamically selects the optimal transmission path through reinforcement learning based on the link fluctuation amplitude index and the fluctuation rule index.
8. The intelligent collaborative management system of a power communication network based on multi-modal awareness and knowledge graph driving according to claim 1, wherein the central intelligent decision-making platform comprises a data center, a knowledge base, a visual cockpit and an intelligent warning engine, and supports multi-modal collaboration and closed-loop management.
9. A working method of an intelligent collaborative management system of an electric power communication network based on multi-modal sensing and knowledge graph driving, which is implemented by adopting the intelligent collaborative management system of the electric power communication network based on multi-modal sensing and knowledge graph driving according to any one of claims 1 to 8, and is characterized by comprising the following steps: the method comprises the steps that firstly, an intelligent circuit arrangement module is used for automatically processing a cable subjected to migration and change; Step two, constructing and updating a power communication equipment knowledge graph through a network dynamic modeling module; step three, service priority scheduling and resource allocation are carried out through a multi-dimensional service cooperative scheduling module; step four, implementing equipment state monitoring and predictive maintenance through an equipment intelligent monitoring and maintenance module; Step five, automatically identifying and early warning the overhaul conflict through an overhaul conflict intelligent identification module; Step six, optimizing a transmission path in real time through an optical transmission path self-adaptive optimization module; and step seven, integrating data of each module by the central intelligent decision platform to realize global situation awareness and intelligent decision.

Description

Electric power communication network intelligent collaborative management system based on multi-mode sensing and knowledge graph driving and working method thereof Technical Field The invention provides an intelligent collaborative management system of an electric power communication network based on multi-mode sensing and knowledge graph driving and a working method thereof, and relates to the technical field of intelligent operation and maintenance of the electric power communication network. Background With the development of a novel power system and an energy internet, the scale of a power communication network is continuously enlarged, the service type is increasingly complex, and the traditional operation and maintenance mode faces the following problems: 1. The line migration and modification depends on manual work, and has low efficiency and poor safety; 2. The network topology is complex, and a dynamic visualization and influence analysis means is lacked; 3. The service scheduling rigidity is difficult to adapt to the differentiated requirements of multiple priority and multiple regions; 4. The equipment monitoring strategy is single, and intelligent and differentiated maintenance cannot be realized; 5. the overhaul conflict identification depends on manual work, and is low in efficiency and easy to make mistakes; 6. The optical transmission path is affected by link quality fluctuation and lacks adaptive optimization capability. The prior art provides solutions to single problems, lacks system-level cooperation and intelligent decision support, and is difficult to realize efficient, reliable and intelligent operation of the power communication network. Disclosure of Invention In view of the above, in order to make up for the blank and the deficiency of the prior art, the invention provides an intelligent collaborative management system of an electric power communication network based on multi-mode sensing and knowledge graph driving and a working method thereof, and the intelligent operation and maintenance from a physical layer to a service layer are realized through the multi-mode sensing and knowledge graph driving. The invention provides an intelligent collaborative management system of an electric power communication network based on multi-mode perception and knowledge graph driving, which comprises the following contents: The invention provides an intelligent collaborative management system of an electric power communication network based on multi-mode sensing and knowledge graph driving, which is characterized by comprising the following components: the intelligent circuit arrangement module is used for automatically cleaning and uniformly winding the cables in the power communication relocation process; The network dynamic modeling module is used for constructing a knowledge graph of the power communication equipment and dynamically reflecting the association degree and influence among the equipment; The multidimensional service collaborative scheduling module is used for carrying out resource collaborative mapping and scheduling based on service priority and region characteristics; the intelligent equipment monitoring and maintaining module is used for realizing equipment classification monitoring, predictive maintenance and operation and maintenance plan dynamic matching; the overhaul conflict intelligent recognition module is used for automatically recognizing time, resource and logic conflict based on the knowledge graph and the attention mechanism; The self-adaptive optimization module of the optical transmission path is used for monitoring the fluctuation of the link quality in real time and dynamically adjusting the transmission path through reinforcement learning; the central intelligent decision platform is used for integrating the modules to realize multi-source data fusion, situation awareness and cooperative control. Further, the intelligent circuit arrangement module comprises a cleaning mechanism, a reciprocating sliding positioning mechanism and a coiling mechanism, and the synchronous cleaning and uniform arrangement of cables in the coiling process are supported. Further, the network dynamic modeling module dynamically adjusts the node mapping area and the edge structure length based on the equipment operation data, and intuitively reflects the equipment state and the association strength. Further, the multidimensional service collaborative scheduling module supports differentiated bearing of control type services and non-control type services, and performs resource mapping based on a regional scheduling rule table. Further, the intelligent equipment monitoring and maintaining module divides the equipment into one class, two classes and three classes, and implements a differential monitoring strategy based on fault history and operation parameters. Furthermore, the overhaul conflict intelligent recognition module optimizes the knowledge graph by adopting a multi-head attent