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

A technology of monitoring system and neural network, which is applied in the field of safety early warning of coal mine monitoring system based on LM neural network, can solve the problems of inability to judge computer virus propagation detection and threat attack, and inability to monitor system safety early warning, so as to reduce potential threats and reduce Operation and maintenance costs and the effect of improving the ability of security early warning

Active Publication Date: 2020-03-17
CCTEG CHINA COAL RES INST
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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, w

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

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Embodiment Construction

[0045] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0046] Such as figure 1 , figure 2 , image 3 , Figure 4 , Figure 5 with Image 6 As shown, a coal mine monitoring system safety early warning method based on LM neural network is based on a coal mine monitoring system including a management client, and the method includes the following steps:

[0047] Step S1: Obtain the monitoring system data collection through the deployment script collection;

[0048] The step S1 acquiring the monito...

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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...

Claims

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Application Information

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IPC IPC(8): H04L29/06G06N3/04
CPCH04L63/1425G06N3/045
Inventor 顾闯连龙飞孟庆勇陈亚科李起伟魏峰
Owner CCTEG CHINA COAL RES INST
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