Research On Construction Method Of Mine Production Equipment Knowledge Base Based On Ontology

Mine safety production depends on accurate identification and positioning,precise control,intelligent decision-making and intelligent collaborative operation of equipment.Due to the complex and changeable underground production environment,the interaction of intelligent equipment has problems such as information is not easy to share and reuse,and information transmission is affected by load and environmental disturbance,which hinder the intelligent and unmanned development of mine production.In order to solve the problems of underground system heterogeneity and information sharing,this thesis is based on the ontology,combines ontology update,edge computing and semantic mapping technology to study the ontology construction method of mine production equipment.In this thesis,considering the importance and complexity of production equipment,hoisting equipment is selected as an example to construct the ontology knowledge base of mine hoist.Firstly,ontology construction methods and tools were analyzed,and "seven-step method" and Protégé ontology construction tools were selected.After that,the ontology design of each component unit of the mine hoist is carried out.Considering the practical application requirements,the modeling process of fault ontology of the mine hoist is elaborated in detail,and the artificial construction of ontology knowledge base is completed to make the information unified.Finally,the consistency detection and fault query function of the ontology are verified,and the quality evaluation of the ontology is completedIn order to solve the problem of poor accuracy and timeliness of manual construction of ontology attribute description,an updated framework of ontology based on distributed knowledge discovery technology was proposed.Firstly,the characteristics of downhole sensing data are analyzed.PCA dimension reduction and K-means clustering algorithm are used to extract data attributes and rules from the sensing data.SWRL,which is well integrated with Protégé tools,is used to label the rules,providing more accurate data attributes and more powerful inference rules for the ontology.At the same time,according to the distributed idea of edge computing,the above process is deployed to the Storm platform to simulate the distributed computing process of multiple nodes on the edge of downhole data,which is of great significance to improve the real-time update speed of ontology database.In order to solve the problem of low efficiency of manual ontology knowledge base construction,a semi-automatic ontology knowledge base construction method was designed.Firstly,the composition characteristics of relational database are introduced from the example of relational database.Then the whole mapping process is described in the form of a diagram.Secondly,according to the single source of relational database,S-R2 R and Mul-R2 R algorithms are designed respectively based on R2 RML.Finally,through verification experiments and algorithm performance tests,according to the mapping generate rules and mapping algorithm designed,the transformation from RDB to RDF is effectively realized,and the ontology knowledge stored in RDF is obtained,which shows the feasibility of the semi-automatic construction method of the ontology knowledge base of mine production equipment.The thesis has 49 figures,17 tables,90 references.