Development And Research Of A Magnesium Alloy Expert System

Magnesium and magnesium alloys have been of tremendous concern and been praised as the "metal materials of the green engineering in the 21st century" due to they have a number of advantages, such as low density, high strength to weight ratio, good electromagnetic shielding characteristics, high elastic modulus and so on. But there still exist many difficulties in the research and production of magnesium alloys. Because of the great complexity and uncertainty of factors in the research and the process of materials, large quantities of experiments and large scale screening have been used for the research of materials, which result in very huge consumption. To improve the efficiency of traditional experimental research, develop new methods and speed up the research progress of magnesium alloys, it has become a new trend that the use of interdisciplinary integration, computer aided design and artificial intelligence in the research of magnesium alloys. As the most active and widest field in artificial intelligence research for applications, expert system is good at dealing with strongly nonlinear relationship. Thus, it is very suitable for the material research areas, where study and process are complex and require extensive experience.In this paper, based on the needs analysis of current research and production of magnesium alloys, a magnesium alloy expert system has been designed and developed, which mainly includes the core knowledge base, database, human-computer interface and data exchange mechanism.In view of the rich data resources with the development of magnesium alloys, the data-based method has been used in this subject. And by using artificial neural network and a new method for optimizing modeling parameters of artificial neural network—all permutations and combinations training of parameters, the network models with relatively high precision have been built, which are the predicted ultimate tensile strength/yield strength/elongation model of wrought magnesium alloys, the predicted ultimate tensile strength/yield strength/elongation model of cast magnesium alloys and the predicted grain size model of cast magnesium alloys. Then, the core knowledge base of magnesium alloy expert system has been formed by all of these artificial neural network models. Based on these network models, the mechanical properties of magnesium alloys and the grain size of cast magnesium alloys can be predicted through exploiting the potential of existing data of magnesium alloys fully. According to the needs analysis of magnesium alloy data and system design, after completion of the conceptual and logical structure of database, the system database has been established by using database management technology. The system database includes data for selecting magnesium alloys, knowledge base information data and user information data. So, the management of system data and the initial selection of magnesium alloys can be carried out.Based on the completion of system knowledge base and database, then according to the goal of overall system design and the modular functional design, a human-computer interface of magnesium alloy expert system has been developed by using the object-oriented programming language Visual C++.Through Matlab engine, the coupling has been achieved by using mixed programming of Visual C++ and Matlab, which is between the human-computer interface of magnesium alloy expert system and the models in knowledge base. The ADO, a method of accessing database in Visual C++, has been used as the connection between the system database and the human-computer interface of magnesium alloy expert system. Therefore, the data exchange of magnesium alloy expert system has been accomplished by the two methods.The established magnesium alloy expert system has met the design expectations, which is stable during operation, has friend man-computer exchange, and can be used flexibly and conveniently. System applications indicate that the predictive values of mechanical properties or grain sizes agree with the experimental ones well and the errors were in the acceptable range as well. Therefore, the magnesium alloy expert system can provide reference and support for the research and production of magnesium alloy preliminary.