Study And Real Time Predication Of BHF Control Law In Intelligent Deep Drawing For A Rectangular Box

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. Due to lack of the skill in real-time monitoring, identifying and predicting, the automation of sheet metal forming can only finish forming process in the light of pre-established work program and process parameters. When material quality and operating condition of manufactured object change or fluctuate, process parameters can't be automatically regulated. The intellectualization of sheet metal forming, which includes 4 basic elements, real-time monitoring, identification, prediction and control, is the crossing subject of control-science and sheet metal forming theory. 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. Most workpieces are non-axial symmetry complex shape represented by rectangular box in engineering practice, so it has much academic value and significance to study intelligent control technology of deep drawing for a rectangular box.Based on the research achievements of intelligent deep drawing for an axis-symmetric part, the key technologies of intelligent deep drawing for a rectangular box are discussed, and the relevant issues to 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 rectangular box, the establishment of the identification model of parameters and theprediction model of optimal technological parameters is dependent upon the level of understanding the forming law for a rectangular box. The finite element method (FEM) simulation as a necessary method is used frequently in this paper. The C-B rule is introduced and two hypotheses are given according to experiments in this paper. At the same time using FEM the wrinkle limit under invariable BHF is studied. Considering the former results of FLD, fracture limit under invariable BHF is studied using FEM. As a result a BHF region is obtained in which flange is not wrinkled and sidewall is not fractured. According to analysis and experiments of sidewall wrinkle and forming quality, a function relevant to forming quality of sidewall is presented based on nodes'mean distance of major stain. When this function is used in analysis of process under invariable BHF or variable BHF, the results is well consistent with experiments. Thus a better curve of variable BHF is obtained under which flange is not wrinkled, sidewall is not fractured and foming quality of sidewall is better. This curve provides the theoretic basis for the intelligent prediction of BHF and the control in real time.The predictive model of BHF is determined by analysis of neural network algorithm. By analyzing the mode of input and output, the number of hidden nodes and the influence of generalized results, the method to solve the question about neural network in intellectualized deep drawing is determined.Real-time monitoring and control depend on the development of data acquisition (DAQ) technology. A portable DAQ system is established by applying virtual instrument control software LabVIEW, data acquisition card and other relevant hardware. Based on the portable DAQ system, the signal acquisition and sensor calibration both get the satisfied speed and precision of signals. In order to realize real-time prediction and control in the process of intelligent deep drawing, the interface program between the signal control and the predictive model of BHF is developed by using the Matlab Script node LabVIEW provides. This is the last module of intelligent control of deep drawing for a rectangular box.