Communication network management monitoring method based on artificial intelligence

Abstract

The invention discloses a communication network management monitoring method based on artificial intelligence, and the method comprises the following steps: 1, carrying out the analysis and processingof a manual operation flow in a mode of simulating a data interface through the artificial intelligence, and replacing the manual operation to automatically log in and enter a network management system; 2, calling an image acquisition tool to perform image acquisition on the current network management system; 3, performing image processing, noise reduction and feature extraction on the acquired image; 4, obtaining and analyzing the parameters through an image recognition algorithm based on a convolutional neural network (CNN), comparing the parameters with a preset threshold value, and judging whether the equipment is abnormal or not; and 5, improving the convolutional neural network algorithm through analysis of the convolutional neural network algorithm and comparison of the image recognition technology so as to improve the image recognition effect. According to the invention, the routing inspection efficiency of the distribution network communication network management can be greatly improved.

Description

technical field [0001] The invention relates to an artificial intelligence-based communication network management monitoring method used in the field of smart grid communication management and control. Background technique [0002] Ensuring the normal operation of power communication network equipment is an important basis for the normal operation and efficient maintenance of the power grid. The communication technologies adopted by various levels and types of power communication networks are basically consistent with the structure of telecom operators, and they all need to discover, identify, and deal with line and equipment failures in the communication network at the fastest speed. For electric power production, in the case of limited staffing, the operation and maintenance personnel of the unit have to monitor more communication network management, and have higher requirements on the timeliness of finding communication faults and the accuracy of judging the cause of the ...