Intelligent analysis system for flow abnormity of power automation system

Abstract

The invention discloses an intelligent analysis system for flow abnormity of a power automation system. The intelligent analysis system is characterized by comprising an early warning rule and strategy module, a real-time monitoring analysis module, a false rejection rate (FRR) analytical reasoning engine module, a cloud reasoning architecture module and a service health analysis module, wherein the early warning rule and strategy module generates early warning strategies aiming at the flow characteristics of the automation system according to abnormity classification and preset rule parameters; the real-time monitoring analysis module implements real-time monitoring and early warning of service flow abnormality based on the service flow data of the automation system by using the system associated early warning strategies; the FRR analytical reasoning engine module intelligently analyzes the solution of the reasoning abnormity based on the flow data, the early warning rules and the abnormity type; the cloud reasoning architecture module provides a more accurate solution by using multi-place deployed system resources and combining the solution of the reasoning abnormity condition; and the service health analysis module analyzes and calculates the service health of the automation system according to the flow state of each composition part of the automation system. The intelligent analysis system is used for quickly analyzing fault problems, providing the feasible solution, improving the work efficiency of maintenance personnel and ensuring normal operation of the network and the system.

Description

technical field [0001] The invention relates to an intelligent analysis and reasoning engine applied to abnormal network traffic in electric power automation systems. Based on the traffic early warning rules and strategies of the business modules of the automation system, the abnormal network traffic of the business modules is analyzed, and the derivation and application are combined with the cloud reasoning framework and the FRR analysis reasoning engine. Solutions for dealing with exceptions, and evaluate the health of the system based on the traffic data, exceptions, load and other information of each business module of the automation system. Background technique [0002] In recent years, dispatching data network applications have developed rapidly, including automatic systems such as protection fault management, fault recording and remote transmission, power collection systems, and dispatching real-time systems. The data network is an important technical platform to supp...

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Problems solved by technology

[0003] At present, network equipment (mainly referring to switches, routers, etc.) Isolation devices are also gradually increasing, but the software configured with the devices can only realize the configuration, maintenance and simple monitoring of the same type of devices, and cannot be associated with business application systems; When the operation is abnormal, there is a lack of necessary means to analyze the cause of the abnormality, locate the source of the fault and the degree of impact on the business system. When dealing with the fault, it is completely based on the personal experience of the operation and maintenance personnel to conduct investigations, and there is a lack of guidance on feasible solutions.

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