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Profile requirements of silicon steel strip are extremely high and the thickness difference of cold-rolled products is usually less than 7 μm, and the profile quality of hot-rolled strip is the key to ensure the thickness difference of cold-rolled products. In order to produce the silicon steel strip with high-precision shape, the concept of quasi-rectangular rolling during hot continuous rolling was put forward; the equipment configuration and technical method of approximate rectangular section control were studied. Through the roughing multi-target load distribution technology and the roll configuration technology for uniform wear of a 4-high rolling mill, the strip crown of transfer bar was reduced and the profile control stability was guaranteed. Configuring variable contact back-up roll technology on all stands in the finishing rolling process, equipped with symmetry variable taper work roll and long-stroke intelligent shifting strategy in the downstream stands, and using side rolling lubrication technology can make the roll wear more uniform, reduce the edge drop of silicon steel strip, improve the profile quality, and make the strip section of finishing exit "quasi-rectangular". In addition, induction furnace and side heater were also equipped to guarantee the temperature uniformity of the strip, so as to improve the stability of profile control. The whole control technology is based on the 1580-mm hot continuous rolling production line, designed, and developed according to the characteristics of equipment and products, and has been successfully applied, which can obtain the approximate rectangular strip section satisfying the flatness quality, and improve the strip section precision of silicon steel and other products.

Controlling the profile and edge drop in the cold rolling process is crucial especially in applications involving silicon steel. In non-oriented silicon steel production, the work rolls shifting control is widely applied in 6-high tandem cold mills and the differences of the control characters of different stands have been gradually recognized. However, because of the lack of research on shifting control effect of separate stands and their influence between each other, controlling the edge drop by cooperatively shifting the work rolls of multiple stands is still impossible, so the mills’ capability is not utilized efficiently. In this study, we develop a finite element method (FEM) model to investigate this issue. Based on the results of the FEM model, we conclude that work roll shifting of different stands leads to the independent control of edge drop, obtain the shifting control effect of different stands to their exit, and the attenuation effects by the following stands. Besides, we deduce that the approach to calculating the edge drop control characteristics should be modified to summation equation of the attenuation effects. The results of an experiment involving 6-high tandem cold mills are in agreement with the results of calculation with the FEM model and we demonstrate the high precision of the FEM model and the reliability of the subsequent analysis. Based on the edge drop control characters established, the control model and the cooperation strategy were designed and applied to the practical production, and significant improvements of edge drop and transverse thickness deviation were obtained.

Automobile and household appliance panels require steel strips with extremely high-quality surfaces. Therefore, an in-depth study of the surface topography transfer of the steel strip during the rolling process is of considerable significance for improving product quality. In this study, the scale-invariant feature transform (SIFT) algorithm is used to realize the large-field stitching and the correspondence measurement of the surface topography of the roll and strip. The surface topography transfer mechanism and microconvex change law during cold rolling are revealed. Further analysis is conducted regarding the effects of different reduction rates and the initial surface topography of the roll on the formation of strip surface topography. Experimental results reveal that the furrow phenomenon occurs during the rolling process owing to the backward slip effect but is eliminated by the elastoplastic deformation of the matrix and the forward slip action. No furrow occurred along the width direction of the strip. With an increase in the rolling reduction rate, the transfer rate increases, and the strip surface topography is closer to the roll surface topography. Under the same rolling roughness condition and a small reduction rate (5%), the transfer degree increases remarkably with a rise in the reduction rate and increases slowly as the reduction rate continues to grow (from 7 to 10%). This study serves as a theoretical basis for the subsequent improvement of the surface quality of cold rolled strips.

A laser-ultrasonic system was established combining an 8 ns width pulsed laser for ultrasound generation and a two-wave mixing (TWM) interferometer for detection. Several Ti-6Al-4V samples were heat treated variously to get different grain sizes. Longitudinal wave back wall echoes were used to calculate the frequency dependent attenuation of ultrasound after the signals were denoised using wavelet transform. A model was built to calculate the log-normal distribution of grain size based on the correlation between the frequency dependent attenuation and the volumetric grain size distribution derived from electron backscattering diffraction data (EBSD) using Schwartz–Saltykov method.

A single average grain size has been used to characterize all grain sizes of polycrystalline materials. However, the grain size distribution also affects performance and quality. A grain size distribution characterization method was investigated based on a machine learning approach using a laser-induced ultrasonic technology. A pulsed laser was used to generate ultrasound inside the specimens and the ultrasonic signals were detected using a two-wave-mixing interferometer. The grain size distribution was quantified using the expectation and standard deviation of the logarithmic normal distribution function. The attenuation coefficients in different frequencies of ultrasonic signals were set as inputs and the expectation and standard deviation of grain size distribution were set as outputs. The grain size distribution prediction model was built with a neural network optimized by the particle swarm optimization algorithm. 90 data samples were selected as training data (75%) to train the characterization model and 30 data samples were set as test data (25%). The method does not require a physical model and avoids the problem of choosing different scattering attenuation mechanisms for grain size distribution. The results show the machine learning method has the feasibility to characterize the grain size distribution.

Adhesive bonding is widely used in the structural assembly of aircraft, and assessing the curing state of the adhesive is important to ensure the safe operation of the assembly. In this paper, the curing process of epoxy resin is monitored by laser ultrasonics. The propagation of ultrasonic waves in a composite structure is discussed, and the curing of epoxy resin and its influence on ultrasonic characteristics are studied. In the fast-drying epoxy resin, the molecular cross-linking rate is fast, the difference of acoustic impedance between the epoxy resin and aluminum gradually decreases, so the transmission coefficient becomes larger and the reflection coefficient decreases. The calculation of absorption attenuation and dispersion should take this change into account. The relationship between amplitude and reflection coefficient is established by far-field ultrasound. The difference in molecular mobility causes the relaxation process, which results in absorption and dispersion of the ultrasonic waves. Making use of the broadband characteristic of laser ultrasonics, the transmission waves are analyzed. As the epoxy resin changes from liquid to solid, the relaxation time is gradually shortened, and the center frequency of the transmitted wave is gradually increased, the absorption attenuation is approximately linear with frequency. The results show that the curing process has a significant effect on ultrasonic characteristics, and laser ultrasonics could be used as an online monitoring method.

Due to its highly favorable physical and chemical properties, titanium and titanium alloy are widely used in a variety of industries. Because of the low output of a single batch, plate cold rolling without tension is the most common rolling production method for titanium alloy. This method is lack of on-line thickness closed-loop control, with carefully thickness setting models for precision. A set of high-precision thickness setting models are proposed to suit the production method. Because of frequent variations in rolling specification, a model structural for the combination of analytical models and statistical models is adopted to replace the traditional self-learning method. The deformation resistance and friction factor, the primary factors which affect model precision, are considered as the objectives of statistical modeling. Firstly, the coefficient fitting of deformation resistance analytical model based on over-determined equations set is adopted. Additionally, a support vector machine(SVM) is applied to the modeling of the deformation resistance and friction factor. The setting models are applied to a 1450 plate-coiling mill for titanium alloy plate rolling, and then thickness precision is found consistently to be within 3%, exceeding the precision of traditional setting models with a self-learning method based on a large number of stable rolling data. Excellent application performance is obtained. The proposed research provides a set of high-precision thickness setting models which are well adapted to the characteristics of titanium alloy plate cold rolling without tension.