Research On Intelligent Recognition And Control Of Flatness For Thin-Gauge Roll Casting

Thin-gauge roll casting is an important and new development in the technology of aluminum industry. And flatness control is the latest research field in the roll casting, which includes flatness recognition and control technology, and it is the key technology to the roll casting technics and product quality.Funded by the industrialization key technology and whole set equipment research of China Special Plan Project—"New Technology and Equipment Manufacture of the Aluminum and Aluminum Alloy Roll Casting"(No.[1998] 1985), this paper research on the roll casting flatness control technology and equipment. After analyzing flatness forming mechanism and flatness control particularity, the flatness control rules are concluded, and the control project are designed; study the rules of parameter densign with artificial intelligence technology of BP Network and Genetic Algorithms in the flatness pattern recognition, the GA-BP flatness pattern recognition models are innovated and improved by the method of optimizing the neural network initial right in multi-dimension; based on the flatness control rules, with the idea of artificial intelligence in predictive control, the GA-BP flatness on-line predictive and control models are formed; design and empolder the main subsystem(flatness measure system, flow control system, data sampling system and software system), integrate the flatness control technology, and apply the flatness control system to the high-speed thin-gauge roll casting line, which is validated by the industry test. All those are very important to the development of the high-speed thin-gauge roll casting both in theory and application. In this paper, the main research work and achievement as follows:1. After analyzing and summarize flatness forming mechanism and flatness control particularity, point out that the flatness problem dose not exist in raw material, while the tempreture field and velocity field are main factors to the flatness, control method has been concluded which take adjusting hot roller flexibility with flow as primary means, and take controlling the outer cooling and balance jar as subsidiary means, on this point, the control project are designed.2. After researching the applicability of the fast BP learning algorithm in the flatness pattern recognition and the effect of main parameter change to therecognition, the basic rules of the parameter designing are put forward, and point out that improving the recognition ability of the un-training samples is the key to BP network flatness pattern recognition.3. Reseach the method that brings the object encapsulation idea of advanced program into the GA optimization process, and establishs the models of optimizing the neural network initial right in multi-dimension, by this method, the GA-BP flatness pattern recognition models are established. Analyze the effect of main parameter change to the optimization's capability, design the GA fit function which involve the training sample errors and test sample errors, find the synthetically training strategy that the fit value evolution can't be too more in process of optimizing the neural network initial right, and the network goal after optimizing must be smaller than before optimizing. Improve the BP network's recognition ability effectively to the un-training samples.4. According to the flatness control project, the process control models are established, introduce the idea of artificial intelligence in predictive control, use the time-lag of flatness control and real-time data of roll casting mearsurement, establishing GA-BP flatness on-line predictive models and control models in roll casting process, which is validated by the off-line simulation.5. To measure the flatness, design a laser scanner that based on a pair of laser bean difference measure theory, it realize that measure flatness and thickness at the same time in low cost and high precision; develop the flow control system, it's core is PLC; make a distributed data sample system which based on management site, master control site and slave sample site; adopt the modularization idea to design the software system of roll casting flatness control; based on above systems, the flatness control technology is integrated.6. With the industrial trail data of High-speed thin-gauge roll casting, to validate the GA-BP flatness models and the online predictive models which have been founded, the industrial trail results indicate that the models are correct, and it established a basic in theory and trails for roll casting flatness control.