| As a branch of plastic working field, sheet metal forming possesses the important place in the industry field of automobile, aviation, instrument and so on. Its state of the art reflects industrial modern level of a country or region in some degree. After the research of automatization and flexible production, the intelligent press forming is the main research object of sheet metal forming. The intellectualization of sheet metal forming includes 4 basic elements, real-time monitoring, identification, prediction and control. According to the characteristics of the initial piece, utilizing physical quantities easy to be measured, material properties and friction coefficient can be determined in real-time, and then the forming process can be completed automatically with the optimal processing parameters. As a result, the intellectualization of sheet metal forming process is the higher level of new technologies such as press forming automation and flexible process system, by which not only can the feature of manufacturing technique be changed, but also the transformation of press equipment can be forwarded. It brings about the progress of sheet metal forming theory and improvement of analysis precision at the same time. it has the important significance for degrading sheet metal level, eliminating technology difficulty between die and equipment adjustment, shortening die setting time, improving productivity and the rate of finished products, and so on. The paper takes the conical part as object of intellectualization deep drawing research. It has much significance to prompt the research of intellectualization deep drawing and popularize its application in the industrial production.Based on the research achievements of mechanical model of the metal sheet deep drawing, the key technologies of intelligent deep drawing for axis-symmetric part are discussed, and the relevant issues to BHF loading model predicting model and controlling in real time have been studied in this paper .Among the four basic elements required by intelligent deep drawing for a axis-symmetric part, the establishment of the identification model of parameters and the prediction model of optimal technological parameters is dependent upon the level of understanding the forming law for a axis-symmetric part. On the specific case of the wall wrinkling in deep drawing, using the energy balance method, the analytical blank holder force(BHF) is gained. The successful deep drawing region is confirmed on the basis of the three limit deformation curves. According to analysis and experiments of forming quality, a better curve of variable BHF is obtained under which flange is not wrinkled, sidewall is not fractured and forming quality of sidewall is better. This curve provides the theoretic basis for the control in real time. On the basis of it, the prediction neural network was founded.Because of the redundancy of training data, it made the convergence of BP neural network slow and imprecision. Using the data reduction and classify function of Rough sets, it can get rid of the training data of surplus attribute and optimize the structure of the neural network. The method to solve the question about neural network in intellectualized deep drawing is determined.The effect of real-time control depends on the development of hardware. The slow-moving effect of hydraulic pressure system brings on discrepancy between the actual control curve and the scheduled control curve. The paper put forward a project to solve the problem. A PIDNN simulation control program has been compiled The PIDNN control system which combines the PID control system and neural network brings a method to solve this problem.In order to realize real-time prediction and control in the process of intelligent deep drawing, the interface program between the identification model and the predictive model of BHF is developed by LabVIEW software. The integration and debugging work of the whole intellectualization control system was finished by combining the DAQ system and the control system.
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