Design And Research Of Coal Mine Monitoring And Early Warning Model Based On Ontology And Association Rules

Coal mine enterprise is the basic industry in China,but coal mining has great risks.Because of the harsh working environment in the mine,insufficient safety technology,and irregular operation,coal mine casualties occur every year.In order to reduce the occurrence of accidents,coal mine monitoring and early warning system is now equipped in most coal mining enterprises.It can not only monitor environmental parameters such as gas and CO,and implement preventive measures such as over-limit alarm and power failure,but also real-time monitor the operation status of various equipment such as air doors and air ducts to ensure their normal operation.Coal mine monitoring and early warning system can improve the safety management ability of coal mine enterprises to a certain extent,but it also has some drawbacks,such as confused information management in the system,a large number of monitoring data are not effectively utilized,and failure to detect sensor insensitivity in time leads to poor reliability of the system.Through the study of the above problems,a coal mine monitoring and early warning model based on ontology and association rules is constructed.This model uses ontology because it can systematically organize the disordered domain knowledge;it can also store and query historical data based on the structural characteristics of ontology;it can also use coal mine monitoring data for ontology reasoning and early warning.It should be noted that the ontology reasoning of this model is based on Jena reasoning machine.The model also applies association rule mining technology,because association rule mining algorithm can process coal mine monitoring data according to their characteristics to get implicit association rules which are valuable for coal mine early warning and apply them to ontology reasoning.The main research contents are as follows:(1)Through consulting documents such as "Coal Mine Safety Regulations" and so on,this paper obtains a large number of relevant terms in the field of coal mine monitoring and early warning.Then this paper uses the seven-step method to deal with these terms to obtain the basic framework of the ontology model,such as concepts,structural relations between concepts,attributes,constraints and examples.Finally,a complete mine monitoring and early warning ontology model is built based on ontology editing tool---Protege.(2)This paper uses association rule mining technology to process monitoring data of coal mine.Traditional Apriori association rules mining method is widely used,but the result of mining is unsatisfactory.Many invalid,false and unsatisfactory rules may be obtained.Therefore,this paper improves the method by adding relevance and interest into Apriori association rule mining method.Experiments show that the improved method is effective and can mine a large number of coincidences.Association rules for user requirements.Based on Jena grammar,association rules are written into customized reasoning rules that meet the requirements.(3)This paper uses Jena inference engine to bind the ontology model and inference rule base of coal mine monitoring and early warning,and then constructs a coal mine monitoring and early warning model based on ontology and association rules.Tests show that the model is effective and feasible,which can improve the accuracy of coal mine early warning to a certain extent,and can reduce the incidence of coal mine accidents.Figure20 Table9 Reference74...