Research On Data Mining Technology And Application For Digital Prototype Performance Simulation Analysis Of Bag Filter

In recent years,with the rapid development of computer technology,digital prototype technology has gradually become the mainstream of innovative research of complex products,and has been widely used in aerospace,automobile,ship and other industries.Digital prototype produces massive heterogeneous data with complex relationship during the digital design,simulation analysis and operation of the complex product whole life cycle.The acquisition of potential knowledge in these data is a difficult problem in product performance analysis and optimization design.Data mining technique can intelligently and automatically extract the hidden valuable information from massive,noisy,incomplete and random data.At present,it has been well applied in engineering diagnosis,public administration,finance,medicine and other fields.The rules of the performance simulation analysis of the bag filter digital prototype can be obtained through data mining technology.And the performance indicators can be rapidly obtained.It is important to optimize design quality,shorten development cycles and reduce development costs.The main contents of the full text include:1.The working process and simulation data characteristics of the self-developed digital prototype of bag filter were studied.The working performance of bag filter and the complexity of related data were analyzed.The data mining target of digital prototype of bag filter was established.2.Combined with the target of data mining of the bag filter digital prototype,the FP-Growth algorithm in association rules was determined.Considering the uneven distribution of attributes in the database,a weighted theory was introduced into the traditional FP-Growth algorithm to improve the real value of the generated rules.The hash function was introduced into the FP-Growth algorithm.And the attributes of each dimension were divided to improve the efficiency of the original algorithm.3.The data mining application system for digital prototype performance simulation analysis of bag filter was developed.The system includes product digital prototype modeling,numerical simulation,data mining and other functional modules.The 192 innovative series bag filter digital prototype was taken as an example.Performed its digital prototype modeling and numerical simulation.Through the data mining module,the improved FP-Growth algorithm was used to mine the potential association rules between the simulation parameter combination and the working performance of the digital prototype.The research shows that valuable potential knowledge can be found by using data mining technology in the digital prototype of bag filter.So that designers can more easily understand the relationship between product parameters and performance,which will have an important reference value for the optimal design of products.