Design Of Cold Rolled Steel Online Monitoring Evaluation And Mode Recognition System

Due to the rapid development of iron steel industry, the steel production increases every year. But in recent years, the lack of advanced process and testing technology in the precise control of the cold rolling mill leads to poor international competitive ability in the field of finished steel. In order to promote the conversion of the high end field, and to improve the productivity and quality, this thesis presents cold rolling process automation, intelligent control and high-precision flatness measurement technology as the design objective. The thesis designs the software system of the online display, collection and evaluation. The software system provides services of visual display, intelligent evaluation and defect identification. The main contexts include:Firstly, the thesis discusses the problem of shape detection and studies the requirement analysis. According to the actual production, the systems businesses are subdivided. Then the hardware and software are selected.Secondly, according to the requirement of measurement, this thesis selects UDP to communicate with the hardware and uses the transaction management. Then the concurrent programming technology is described, the thread pools is used.Thirdly, the thesis makes depth analysis on the test principle of the strip rolling and builds the mechanical model of the quality evaluation. Then the use of polynomial fitting and BP neural networks is studied.At last, the central management platform is complete designed. The software system provides data pretreatment, visual display, dimensional analysis, pattern recognition, interface beautification, system operation and communication protocol. Then it is tested on the integrative detection platform.In this thesis, the system of data collection and evaluation is designed. The results of the test show the system has the ability of accurate monitoring and specialized analysis. On the one hand, this study avoids the uncertainty of the complicated data processing; on the other, it effectively improves the feedback rate of cold rolling process and guarantees the timeliness of closed-loop control. This study has wide range of potential applications and important reference values for cold rolling process.