Research On Knowledge Service Method Of Railway Electric Maintenance Based On Uncertainty Rule Reasoning

As the backbone of modern comprehensive transportation system,railway is an important infrastructure and economic lifeline of the country.In recent years,with the continuous advancement of railway modernization and leaping development in China,the train speed has been improved,the scope of operation has been expanded,and the requirements for safety have become more and more strict.As the key to ensure railway transportation safety and improve transportation efficiency,signal equipment is particularly important to ensure the safety and reliability of its operation.At present,the main mode of electrical maintenance is that the field personnel maintain the equipment according to the maintenance plan.It is difficult to obtain the effective knowledge resources quickly and accurately due to the complex types of equipment under jurisdiction.Therefore,how to make the electrical knowledge resources provide better service for the electrical maintenance work,improve the efficiency of railway electrical production,maintenance,management and other business,and realize the informatization,integration and intelligence of electrical maintenance has become an urgent problem for the railway electrical department.This paper takes the knowledge service method of railway electrical maintenance as the main research content,and constructs a kind of knowledge active push service which is driven by business process and knowledge demand and integrates human,process and knowledge.On this basis,a multi-dimensional and multi condition cloud mapping uncertain rule reasoning method of knowledge service is proposed,so as to realize the on-demand push of complex decision-making of electric maintenance operation.First of all,based on the introduction of the organization structure and main work of the electrical department,this paper analyzes the domain knowledge scope of the electrical equipment maintenance,describes the knowledge network from the enterprise knowledge node and the alliance knowledge node level respectively,integrates the maintenance knowledge and the maintenance business,constructs the electrical equipment maintenance knowledge network model,and realizes the electrical knowledge oriented to the maintenance business resource management.Secondly,on the basis of the knowledge network,the knowledge active push service architecture based on business process is designed.Based on the analysis of the work flow of the maintenance of the electric equipment,the process modeling method based on the activity network is used to design the model for the work process of the maintenance of the electric equipment.Combined with the knowledge matching method based on the similarity algorithm,the active knowledge push based on the business process and knowledge flow is realized.Then,in view of the situation that the maintenance personnel can not solve the complex fault,the decision-making model of railway signal equipment maintenance based on uncertainty rule reasoning is established.The uncertain knowledge in the rule base of signal equipment is quantitatively described by using the cloud model,and the uncertain reasoning process is realized by the multi-dimensional and multi rule cloud generator algorithm,so as to obtain the equipment failure mode and output the maintenance scheme corresponding to the maintenance opinion.The validity of the algorithm is verified by taking 25 Hz phase sensitive track circuit as an example.Finally,based on the research of the key technology of the above-mentioned electrical knowledge service,the design and development of the railway electrical auxiliary decision-making prototype system is completed,which verifies the feasibility and effectiveness of the model and method designed in this paper.