Coal mine monitoring system safety early warning method based on LM neural network

Abstract

The invention discloses a coal mine monitoring system safety early warning method based on an LM neural network. The method comprises the following steps of acquiring a monitoring system data set by deploying a script set; establishing a logic mapping file of the distributed database and the monitoring system data set; normalizing the logic mapping file to form a sample library; establishing a trend analysis model based on LM neural network deep learning according to the sample library; acquiring monitoring system data in real time, transferring the monitoring system data into a logic mappingfile, inputting the logic mapping file into an LM neural network for analysis, and comparing the logic mapping file with the trend analysis model; judging whether abnormity occurs or not according toa comparison result, and if abnormity occurs, giving an alarm prompt.According to the invention, a safety early warning function can be realized for the monitoring system, potential threats caused byhuman participation are reduced, early sensing of network data situation changes of the monitoring system is realized, the safety early warning capability is improved, and the operation and maintenance cost of the protection system is reduced.

Description

Technical field [0001] The invention relates to the technical field of safety monitoring, in particular to a coal mine monitoring system safety early warning method based on LM neural network. Background technique [0002] At present, the network security early warning methods of underground monitoring systems in coal mines are mostly based on prefabricated security policies at the network boundary or at the exit of key equipment to perform gateway-type traffic filtering. In the long-term operation of the monitoring system, the routine maintenance of gateway-type protective equipment And security policy upgrades have high cost and insecurity problems. E.g: [0003] Scenario 1: The monitoring system has been operating in the underground for a long time. It needs to share the industrial ring network operation with multiple systems such as underground production and personnel positioning. The security of the monitoring system may be affected by the intrusion of ring network shared eq...

AI Technical Summary

Problems solved by technology

This method has the following defects: First, all other systems in the ring network that are directly or indirectly related to the monitoring system need to deploy safety protection equipment, and it is necessary to filter, analyze and give early warning of all system network data in the coal mine, which is prone to security protection loopholes , it is impossible to provide targeted monitoring system for safety warning

In this way, there are problems such as the spread of computer viruses that are difficult or even impossible to judge, or the detection and threat attacks from external networks.

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