新型高性能电工材料应用特性模块化与自学习建模技术分析-analysis of application characteristic modularization and self-learning modeling technology for new high performance electrical materials.docxVIP

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新型高性能电工材料应用特性模块化与自学习建模技术分析-analysis of application characteristic modularization and self-learning modeling technology for new high performance electrical materials.docx

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新型高性能电工材料应用特性模块化与自学习建模技术分析-analysis of application characteristic modularization and self-learning modeling technology for new high performance electrical materials

modeling takes comprehensively into account the linearity, dimension, operational state, coupling factor, coupling method and numerical method. In order to achieve a relatively strong independence of the module with less data dependency and redundancy, the engineering fuzzy judgment method has been used in the module mergence. Finally seven modules are obtained: physical effect modular, dimension modular, linearity modular, operational state modular, coupling factor modular, coupling method modular and numerical method modular. Numerical packages for the modular design of new high-performance electromagnetic materials are coded and implemented.3．A self-learning mechanism is introduced in the modeling and characterization.Theself-learning function has adaptive, optimal and intelligent feature according to the characteristics of modeling. The expert system is further introduced into the modeling techniques with self-learning function. Based on the rules of expert system, the numerical packages for modeling the new high-performance electromagnetic materials are designed.4．Taking the design of giant magnetostrictive acceleration sensors as an example, themodular design techniques have been integrated to the design of the knowledge library of magnetostriction transducers. Giant magnetostrictive acceleration sensors is modeled and analyzed by the developed modeling and analying software of new high-performance electromagnetic materials. Considering the multi-physical-discipline properties based on the inputed parameters, the strongly magnetic-mechanical coupling characteristics of the giant magnetostriction are modeled and analized besed on the rule base; and the self-learning function is realized.KEY WORDS: new high-performance electromagnetic materials, practical characteristics modeling, modularity, self-learning, giant magnetostriction, acceleration sensorsiv河北工业大学博士学位论文第一章绪论从 20 世纪下半叶开始的新技术革命，新材料已成为各高技术领域发展的突破口，并在很大程度上影响了新兴产业的发展进程。在材料技术领域，高温结构材料、多功能材料、超导材料、激光材料、生物材