Application of a new feature extraction and optimization method to surface defect recognition of cold rolled strips

Considering that the surface defects of cold rolled strips are hard to be recognized by human eyes under high-speed circumstances, an automatic recognition technique was discussed. Spectrum images of defects can be got by fast Fourier transform （FFF） and sum of valid pixels （SVP）, and its optimized center region, which concentrates nearly all energies, are extracted as an original feature set. Using genetic algorithm to optimize the feature set, an optimized feature set with 51 features can be achieved. Using the optimized feature set as an input vector of neural networks, the recognition effects of LVQ neural networks have been studied. Experiment results show that the new method can get a higher classification rate and can settle the automatic recognition problem of surface defects on cold rolled strips ideally.

Online application of automatic surface quality inspection system to finishing line of cold rolled strips

An automatic surface quality inspection system installed on a finishing lineof cold rolled strips is introduced. The system is able to detect surface defects on cold rolledstrips, such as scratches, coil breaks, rusts, roll imprints, and so on. Multiple CCD area scancameras were equipped to capture images of strip surface simultaneously. Defects were detectedthrough 'Dark-field illumination' which is generated by LED illuminators. Parallel computationtechnique and fast processing algorithms were developed for real-time data processing. Theapplication to the production line shows that the system is able to detect defects effectively.

Surface Inspection System for Cold Rolled Strips Based on Image ProcessingTechnique

A new surface inspection system for cold rolled strips based on image processing is introduced. The system is equipped withtwo different illumination structures and CCD matrix cameras. The structure and image processing of the inspection system are described. Some efficient algorithms for image processing and classification are presented. The system is tested with strip samples fromcold rolling plants. The results show that the system can detect and recognize six common defects of cold rolled strips successfully.

Applied principle of minimum potential energy in analyzing buckle phenomenon of cold rolled strip

When solving buckling type based on minimum potential energy, it is first to make hypothesis for strip buckling type. Under the simple strain condition, buckling type and strain distribution have a certain similarity, so the hypothesis is reasonable comparatively. However, under the complicated strain condition, it is difficult to give more reasonable buckling type. Moreover, the existing algorithms usually ignore the effect which the transverse stress and the shear stress have on the buckling type. After assuming strip was only affected by shear stress for the edge wave and affected by both transverse stress and the shear stress for the center wave in the paper, the buckling form of strip under simple strain situation was calculated. It was seen from the calculating result that wave height and half wavelength were smaller than those of the existing algorithms, and the wave height and half wavelength of edge wave were all bigger than those of center wave in the same stress distribution. Secondly, a more reasonable hypothesis method of buckling type for the complicated stress distribution was put forward. After analyzing, the result showed that it was more reasonable by using the optimizing algorithm.

Intelligent representation method of image flatness for cold rolled strip

Real flatness images are the bases for flatness detection based on machine vision of cold rolled strip.The characteristics of a real flatness image are analyzed,and a lightweight strip location detection(SLD)model with deep semantic segmentation networks is established.The interference areas in the real flatness image can be eliminated by the SLD model,and valid information can be retained.On this basis,the concept of image flatness is proposed for the first time.An image flatness representation(IFAR)model is established on the basis of an autoencoder with a new structure.The optimal structure of the bottleneck layer is 16×16×4,and the IFAR model exhibits a good representation effect.Moreover,interpretability analysis of the representation factors is carried out,and the difference and physical meaning of the representation factors for image flatness with different categories are analyzed.Image flatness with new defect morphologies(bilateral quarter waves and large middle waves)that are not present in the original dataset are generated by modifying the representation factors of the no wave image.Lastly,the SLD and IFAR models are used to detect and represent all the real flatness images on the test set.The average processing time for a single image is 11.42 ms,which is suitable for industrial applications.The research results provide effective methods and ideas for intelligent flatness detection technology based on machine vision.

Prediction of mechanical properties of cold rolled strip based on improved extreme random tree

Taking the 2130 cold rolling production line of a steel mill as the research object,feature dimensionality reduction and decoupling processing were realized by fusing random forest and factor analysis,which reduced the generation of weak decision trees while ensured its diversity.The base learner used a weighted voting mechanism to replace the traditional average method,which improved the prediction accuracy.Finally,the analysis method of the correlation between steel grades was proposed to solve the problem of unstable prediction accuracy of multiple steel grades.The experimental results show that the improved prediction model of mechanical properties has high accuracy:the prediction accuracy of yield strength and tensile strength within the error of±20 MPa reaches 93.20%and 97.62%,respectively,and that of the elongation rate under the error of±5%has reached 96.60%.

Application of automatic surface inspection system in cold-rolled strip production

The detection and classification of real-time surface defects play an important role in automotive sheet inspection and production. In this paper, an automatic surface inspection system （ASIS） based on signal processing in Baosteel NO. 4 cold-rolled plant is briefly presented. We demonstrate that the strip surface defect properties such as image, type, pitch, and position can be accurately calculated and classified by the automatic surface inspection system. In the manufacturing of the high-quality cold-rolled strips, it is necessary that the real-time surface defects can be detected and transferred by the automatic surface inspection system combined with annealing lines and recoiling lines.

Fatigue Property of Hot Rolled and Cold Rolled Strips

Tension-tension fatigue properties of hot rolled and cold rolled strips with same contents and sizes were measured by using group test method at room temperature in air. The results showed that the fatigue properties of the hot rolled strips were obviously higher than those of the cold rolled strips. The hot rolled strips with similar or higher tensile strength exhibited superior fatigue property over the cold rolled strips. Fracture morphologies observed using scanning electronic microscope （SEM） showed that the hot rolled strips exhibited larger fracture areas, indicating a slightly lower plasticity, and more even fracture microstructure and stable properties. It is feasible and reliable to replace cold rolled strips with hot rolled strips.

Research and Development Trend of Shape Control for Cold Rolling Strip

Shape is an important quality index of cold rolling strip. Up to now, many problems in the shape control domain have not been solved satisfactorily, and a review on the research progress in the shape control domain can help to seek new breakthrough directions. In the past 10 years, researches and applications of shape control models, shape control means, shape detection technology, and shape con- trol system have achieved significant progress. In the aspect of shape control models, the researches in the past improve the accuracy, speed and robustness of the models. The intelligentization of shape control models should be strengthened in the future. In the aspect of the shape control means, the researches in the past focus on the roll opti- mization, mill type selection, process optimization, local strip shape control, edge drop control, and so on. In the future, more attention should be paid to the coordination control of both strip shape and other quality indexes, and the refinement of control objective should be strengthened. In the aspects of shape detection technology and shape control system, some new types of shape detection meters and shape control systems are developed and have successfully indus- trial applications. In the future, the standardization of shape detection technology and shape control system should be promoted to solve the problem of compatibility. In general,the four expected development trends of shape control for cold roiling strip in the future are intelligentization, coordi- nation, refinement, and standardization. The proposed research provides new breakthrough directions for improv- ing shape quality.

Industrial shape detecting system of cold rolling strip

A high-precision shape detecting system of cold rolling strip is developed to meet industrial application, which mainly consists of the shape detecting roller, the collecting ring, the digital signal processing （DSP） shape signal processing board and the shape control model. Based on the shape detecting principle, the shape detecting roller is designed with a new integral structure for improving the precision of shape detecting and avoiding scratching strip surface. Based on the DSP technology, the DSP shape signal processing circuit board is designed and embedded in the shape detecting system for the reliability and stability of shape signal processing. The shape detecting system was successfully used in Angang 1 250 mm HC 6-high reversible cold rolling mill. The precision of shape detecting is 0.2 I and the shape deviation is controlled within 6 1 after the close loop shape control is input.

Transverse Distributions of Front and Back Tension Stresses in Cold Strip Rolling

In this paper,such a new lateral displacement function is proposed that the lateral flow velocity is con- tinuous at the entry and the exit of deformation zone.A new kind of finite strip method—the third power B-spline finite strip method—is put forward to simulate strip rolling process.Front and back tension stresses are formulated.The computed results of the transverse distributions of the front and back tension stresses are close to the experimental results.The paper lays a foundation for further analysing the three-dimensional stresses and deformations of strip rolling.

Analysis of the cause of crack in cold rolling of QSn6.5-0.1 strip

In order to know the cause of cracks in cold rolling of QSn6.5 0.1 copper alloy strip, a lot of experiments and analysis were done. The microstructure changes of QSn6.5 0.1 were investigated by means of metallurgical microscope. The morphology of cracks and surface defects were examined using scanning electron microscope. Macroscopic residual stresses produced in every process during manufacturing in the QSn6.5 0.1 strip were measured by X ray diffraction method and hole drilling method. The results show that the cracks in the QSn6.5 0.1 cold rolling strip were caused due to the derivation of metallurgical defects, such as SnO 2, S, fine looses,the inverse segregation unable to clear up when milling, and the accumulation of all kinds of resi dual stresses. When the accumulation of the residual stress reaches the material′s breaking strength, the cracks will be generated. Several measures to avoid the development of these kinds of cracks were put forward, such as: controlling the casting technology, improving homogenization annealing procedure (680 ℃/7 h) and milling quality(using the second milling when necessary), working out a more reasonable rolling technology to ensure intermediate annealing in time.

STUDY ON STRIP AND ROLL DEFORMATION COUPLING OF COLD STRIP ROLLING ON 4-H MILL

The cold strip rolling process on a 4 h mill is studied by coupling the 3 dimensional plasticity deformation of the strip with the elastic deformation of the rolls. On the conditions of that the width to thickness ratio of the strip is 660 and the exit strip shapes are respectively edge wave, centre wave and good, the computed results of the transverse distributions of the roll gap, the rolling pressure, the inter roll pressure, and the front and back tension agree with the experimental results well. The studing methods and the studied results are of great importance to forming shape theory and guiding the development of shape control technology.

STUDY OF THE 3-DIMENSIONAL STRESSES OF COLD STRIP ROLLING UNDER CENTRE WAVE

On the conditions ofthe width to thickness ratio 625 and the centre wave the 3-dimensional stresses distributions of cold strip rolling are studied by using the third power spline function finite strip method. The computed results of the rolling pressure, the 2-directional friction stresses and the front and back tension stresses agree with the experimental results well. In this paper, the frictional stresses of stagnation zone are computed by using preliminary displacement principle and the computing precision is improved.

Compensation Model for Shape Measuring of Cold Strip Rolling

Some unavoidable factors in the process of cold strip shape measurement interfere with the shape meter, so the shape measuring results cannot reflect the true shape of the strip and the measuring precision is low. The influ- ences of the measuring error of the strip edges, the transverse temperature difference of the strip, the deflection of shape detection roller, and the shape of the strip coil on the shape measuring results were analyzed in detail, and the corresponding compensation models were established. The simulation calculation and analysis were carried out on a cold strip mill, and a number of disciplinarian cognitions were obtained.

Effect of Width-to-Thickness Ratio and Thickness Profile Changing on the Critical Instable Shape During Cold Strip Rolling

Based on the volume constancy with equal flow-per-second and elastic sheet stability theory, a coupling relationship among lateral thickness difference, width-to-thickness ratio of cold rolling strip steel under ideal and actual working conditions, and shape is concluded according to the comprehensive influence principle of various factors on the critical instable shape analyzed in-depth. Firstly, the influence model under actual working condition is developed by referring to the basic relationship between lateral thickness difference and shape under ideal condition. The test results prove that for thin strips with thickness below 0.3 mm, their lateral thickness differences have significant effect on the shape. After then, the combined influence of lateral thickness difference and width-to-thickness ratio on the critical instable shape is concluded according to the elastic sheet stability model, with the synthetic effect of these three factors analyzed. Test data indicate that for cold rolling strip steel with width-to-thickness ratio above 3 000, the critical instability stress difference decreases significantly. Actual measurements are conducted on the lateral thickness differences of two rolls of typical strip manufactured by a sixhigh cold mill, with the influence law of lateral thickness variation and width-to-thickness ratio comprehensively investigated. It is demonstrated that during the production of ultrathin strip steel with different width-to-thickness ratios, the loading roll shapes should be fine adjusted according to the lateral thickness difference of input strips.Therefore, the variation of lateral thickness difference of output strips can meet the requirement of shape stability,so as to obtain fine shape.