Research On Knowledge Base And Decision Inference In Expert System Of Solid Rocket Motor Grain Design

The shape and geometric parameters of Solid Rocket Motor(SRM)grain can determine the change rule of gas generation rate in motor with time,and then determine the change of motor working pressure and thrust with time,so grain design is one of the core parts of SRM design.There is a lot of experience knowledge in grain design process.In traditional design,the reuse of design knowledge is realized through scheme comparison and theory,which requires high experience but low efficiency for designers.Based on the key technology of expert system construction and the basic theory of SRM grain design,this paper introduces the Artificial Neural Network(ANN)technology into the expert system of grain design,researches and explores the knowledge base and decision inference algorithm,and then develops the corresponding expert system software.Firstly,this paper studies the knowledge representation method of SRM grain design adapted to neural network model,gives the knowledge representation of single-grain type case,and realizes the knowledge representation of multi-grain type case by using object-oriented technology.The knowledge base is organized,stored and managed in the form of relational database.Secondly,the decision inference algorithm based on artificial neural network technology is studied.The structure and parameters of the ANN with the single-grain were designed,and the training was completed in the sample composed of the simulation data calculated by the combustion surface transition program.The network structure and parameters were adjusted according to the training results,and the performance of the model was optimized.According to the design requirements of expert system,two structural schemes of combination model are proposed,and their ANN model have been designed and optimized.According to the verification results of grain design examples,the predicted errors of these models basically meet the requirements of grain preliminary design,which indicates that ANN is feasible and practical in SRM grain design expert system.The expert system is used to assist the SRM grain design,which can reduce the dependence of grain design on expert experience and reduce the experience requirements for designers.The decision inference algorithm based on ANN makes full use of the existing grain design knowledge,the optimized ANN model can quickly calculate the recommended grain design scheme,obtain more accurate results,and improve the efficiency and design level of SRM grain design.Finally,this paper completes the development of expert system software on the Windows platform,including database management,charge design reasoning,model retraining,etc.SQL Server is used create the database,Python completes the design of human-computer interaction interface,which realizes the basic functions of the SRM grain design expert system software.