Research On Matrix Model Of Shape Control For Cold Strip Mills

In this paper, author chooses research on matrix model of shape control for cold strip mills as the research subject and done deep theory research on flatness pattern recognition, flatness control and section configuration control, achieving new research findings. Flatness pattern recognition is an important part of flatness control system. Considering the practical situation of modern mills with many different flatness control means, a new flatness pattern recognition method including the cubic flatness is brought forward. Using the Legendre polynomial regression method based on least square theory, the model processes with the original flatness data by wavelet de-noising techniques with linear, quadratic, cubic and biquadratic Legendre orthogonal polynomials as basic patterns. The model increases the precision of flatness pattern recognition, makes the results of flatness pattern recognition self-contained, refines flatness control target and makes for increasing the precision of flatness control.Taking HC mill for example and using tilting roll, bending work roll, asymmetry bending work roll and shifting intermediate roll as flatness control means, the effective coefficients on the linear flatness, the quadratic flatness, the cubic flatness and the biquadratic flatness for different control means are calculated by theory model in order to analyse the effective rules on flatness control effective matrix for different flatness control means, which opens out the effective rules on different order flatness for different control means and provides the foundation for the building and realizing on-line flatness control.In order to increase the precision of flatness control, considering the direction of rolling process essence and the direction of measured data, the theory-intelligent dynamic effective matrix flatness control model is built by using theory and intelligent methods synthetically. The network model for rapid calculating theory effective matrix is built by the BP network optimized by particle swarm algorithm, realizing the rapid calculation of theory effective matrix and avoiding the problem that theory model can not meet the need of rapid on-line calculation. The network model for rapid calculating survey effective matrix is built by the RBF network optimized by cluster algorithm, realizing the rapid calculation of survey effective matrix. The model can track practical situations by on-line self-learning with the measured effective data as samples. The scheme for flatness control quantity calculation is established by combing theory control matrix and survey control matrix, improving the commonality, flexibility and precision of on-line flatness control model. In order to increase the precision of strip section configuration control, the effective matrix control mode for strip section configuration control is brought forward for the first time. Using linear, quadratic, cubic and biquadratic orthogonal polynomials describing strip section configuration precisely, the model provides the conception of the effective matrix for section configuration control and builds the control equation for section configuration control by the theory of effect function method, which provides a new method for strip section configuration on-line control. The effective coefficients on section configuration for different control means are calculated by theory and the effective rules on section for different control means are analysed, which provides basis for establishing strip section configuration control strategy. In order to realize rapid calculating the effective matrix for section configuration control, the rapid prediction model for strip section configuration is built by BP network, making the effective matrix model for strip section configuration can be used in on-line section configuration control conveniently.Using theory-intelligent dynamic effective flatness control model and section configuration effective matrix control model synthetically, flatness and section configuration integration control scheme is built in order to enhance flatness and section configuration control capability of tandem mill, which makes on-line flatness control cooperate with on-line section configuration control and realizes the parallel control of different stands. According to the measured flatness and section configuration data of the 1550 tandem mill, the control scheme is validated and the result indicates that the scheme has high flatness and section configuration control precision with a steady and reliable control process and upgrades the control capability of tandem mill with much significance for increasing product quality.Choosing research on matrix model of shape control for cold strip mills as research subject, author has done deep theory research on flatness pattern recognition, flatness control and section configuration control and done relevant simulation analysis and industry validation. New research findings are acquired, which has much significance for the development of flatness and section configuration control theory.