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The control of surface roughness is of great significance for measuring the quality characteristics of cold-rolled steel strip. At present, the conventional method is used to monitor the surface roughness of steel strip by random sample inspection, off-line analysis and test, and on-line adjustment of production process, but the method is of some hysteretic nature and discontinuity. To this end, the paper presents an on-line intelligent control method for surface roughness of the cold-rolled steel strip, adjusting parameters of the skin-pass process in real time and reducing the fluctuation of surface roughness of strip steel. To establish the fuzzy neural network control model of the corresponding relationship between the parameters of the skin -pass process and the surface roughness of steel strip, the deviation between the online detection value and the target value of the surface roughness is taken as the input of the model, so is the differential value of deviation. In addition, the skin -pass rolling force is used as the output. Learning and training fuzzy neural network to get a fuzzy neural network online prediction control model that is applied to continuous treatment unit for cold rolling strip steel. By measuring the surface roughness of steel strip, the system adjusts the skin-pass rolling force in real time. At the same time, to keep the mechanical properties of the steel strip and the strip shape, the system optimizes skin -pass rolling tension and bending force accordingly to realize on -line intelligent control for the surface roughness of steel strip. The proposed system can improve the control accuracy of surface roughness, which can even better satisfy the requirements of downstream users.

This paper proposes an automatic control strategy of the strip width in cold rolling process. The prediction model for the exit strip width of each stand is established. In addition to the strip width variation of the incoming hot-rolled material between the measured and the pre-set values, the variations of the rolling force, tension, bending force and the roll shift amount of each stand are utilized to model and forecast the stand exit width deformation. Then, the model can be used to determine the compensation values of the different profile adjustment mechanism and the exit strip width can be controlled in high accuracy. In this way, the effect of the strip width variation of the incoming hot-rolled material and the fluctuation of the stand rolling process parameters on the exit strip width can be eliminated. Moreover, the feed-forward control of the strip width can reduce the incidence of abnormal situation, such as the strip breakage and off-tracking ,and improve the stability of the cold rolling process.

An automatic control method to prevent thin strip steel from breaking in cold rolling is presented in this paper. The strip width detector is equipped at the entry and exit sections of the cold rolling mill respectively, thus the width reduction of the strip steel before and after the mill can be real-time detected . The signal of the width reduction rate exceeding a certain value means that the strip edge is too tight. Then, via the strip shape adjusting mechanism, the edge of the strip steel becomes loose and the strip breakage can be avoided. By applying this method, the incidence of strip breakage can be reduced and the productivity capacity can be increased, and more, the width control accuracy of the rolled steel strip can be improved. The validity of the proposed method is verified by the example simulation.

This paper firstly analyzes the problems that exist in the cold rolling of steel industry. Secondly, a new approach is proposed to temper and straighten the strip steel based on the temper leveling mill, shortly, TLM. The required high quality of the wave, surface and mechanical properties can be achieved only with TLM. TLM holds the functions of both temper machine and straightening mill and can produce good quality strip steel, no only the waviness, mechanical properties, but also the surface quality. The usage of TLM can lower the cost of the production of tempering, straightening and equipment investment.Finally, the experiments are done and verify the validity of the approach.

A feed-forward control method for cold rolled strip flatness is put forward. That is to carry out feed-forward compensation to bending force of the stand, so as to mitigate the complex influence caused by changes of rolling force and tension in rolling process on strip flatness based on regular flatness feedback control which focus on the last stand, according to changes in stand rolling force, inlet tension and outlet tension measured. Result shows that this technique not only increased the flatness quality of the strip cold-rolled, but also increased the stability of cold-rolling process of thin strip when it was actually applied in a cold tandem mill.

A roll shape setting model was built for the hot galvanizing and planishing mill. The uniform transversal distributions of the front tension in the exit and the unit pressure were considered as the objective function. At the same time, the quality of the products, the stability of zinc layer, and the homogeneity of spangles were of considerable significance in the planishing process. The model was applied to the roll shape setting of the 1800 cold rolling 3# CGL hot galvanizing and planishing mill of Baosteel Co Ltd. After being planished, the flatness of a strip that was less than 6 I was more than 97%, and the flatness of others were less than 10 I; the pass percentage of the zinc layers reached 100%.