Research On Intelligent Analysis And Processing Technology Of Coal Mine Safety Monitoring Data

Coal is the main energy source in China.Coal mining accidents occur from time to time during mining.In recent years,the death rate of one million tons of coal in China has declined year by year,but the security situation is still severe.Coal mine safety monitoring system is a crucial tool and means to ensure safe production.In order to prevent accidents,the state and coal mining enterprises put forward higher requirements for the monitoring system,and the coal mine monitoring system is developing toward intelligence,accuracy,and efficiency.How to use the massive data monitored by the monitoring system to acquire unknown knowledge has become the key to the intelligence of coal mine monitoring systems.This paper comprehensively applies the theories and methods of safety science,monitoring technology,artificial intelligence theory,accident prediction theory,computer technology and network technology and other related disciplines,and integrates security method optimization methods to study the issue of coal mine safety intelligent monitoring.First of all,statistics on the accidents and causal factors of 107 lifting and extraordinarily large coal mine accidents occurred in China from 2008 to 2017 were analyzed.Based on the analysis of coal mine accident causes,combined with intelligent monitoring technology,a coal mine intelligent safety monitoring model based on information acquisition module,control module and knowledge acquisition module was proposed.The working principle of the model is introduced in detail.Through the sensor monitoring information and the manual input information,the risk analysis is performed according to the established prediction algorithm,and the result of the intelligent warning is analyzed and the decision is provided.Then,two key algorithm methods in the intelligent monitoring model of coal mines,namely,mass data prediction algorithm and countermeasure optimization method,are studied.Based on the grey system and neural network theory,a GM(1,N)_GRNN prediction algorithm model was constructed.The example of gas emission was verified in practical engineering applications.Using the analytic hierarchy process to design the optimal method of interval multi-attribute countermeasures,taking the gas explosion accident as an example,the gas accident safety countermeasures database was established and examples were optimized.Finally,using ASP language,developed the coal mine intelligent security monitoring system,realized the monitoring information management of coal mines,intelligent prediction and early warning analysis of coal mine accidents,and obtained the knowledge of massive data hiding,and provided managers with the function of decision-making assistance.The research work in this paper has a clear theoretical significance and has practical significance in coal mine accident prevention and safety management.