Grain-oriented silicon steel is a metallic soft magnetic material with sharp Goss texture ({011}〈100〉). The formation and evolution of Goss texture run through the whole process of hot rolling, normalizing, cold rolling, decarburization annealing and high temperature annealing. Based on “heredity” characteristics of microstructure and crystallography orientations, the origin and evolution of Goss texture in grain-oriented silicon steel are systematically reviewed in this paper. During the hot rolling stage, the Goss texture originates from shear deformation in the subsurface of the hot rolled plate, with the primary cause being the uneven shear strain along the plate thickness direction induced by friction between the rolls and the plate surface. Normalization treatment was used to “filter” and “strengthen” the Goss “seeds” initially formed in the hot-rolled sheet, and the precipitation state of the inhibitor and the distribution of grain boundary characteristics were optimized. During the cold rolling process, the majority of Goss orientations transform into γ-fiber texture, while a small portion of the orientation “seeds” remains in a metastable state within the shear bands and deformation bands. The decarburization annealing treatment induces recrystallization in the cold-rolled matrix, and the “residual” Goss orientation “seeds” nucleate within shear bands and deformation bands, where it is “reconstructed” into Goss-oriented grains with abnormal growth potential. In the high temperature annealing stage, a small number of Goss grains grow abnormally in the inhibitor pinned matrix, and finally form a sharp Goss texture. Regarding the mechanism of abnormal growth of Goss grains, the academia has successively proposed the coincidence site lattice grain boundary (CSL) theory, the high-energy grain boundary (HE) theory and the solid-state infiltration (SSW) theory. The three theories explain the selective growth mechanism of Goss grains from the perspective of grain boundary structure, grain boundary energy and grain boundary energy anisotropy, but they are still controversial. In this paper, the research context of this direction is systematically sorted out to provide reference for process optimization and theoretical innovation of high-performance grain-oriented silicon steel.

Taking phosphate and ammonium metavanadate as the primary raw materials, a low-chromium phosphate coating solution was prepared for grain-oriented silicon steel with a magnesium silicate underlayer. Upon heat treatment at over 800℃, the prepared coating solution develops a compact and dense insulating film. Phase composition analysis reveals that the coating consists of amorphous oxides or composite oxides of aluminum, silicon, magnesium and vanadium, along with a small amount of phosphorus-containing oxysalts. The grain-oriented silicon steel specimen with low chromium insulating coating exhibit excellent corrosion resistance in 3.5%(mass fraction) NaCl solution. Polarization curve analysis shows that the self-corrosion potential of the low chromium coated sample is -0.563V, and its polarization resistance R_p is up to 24425.5Ω. Electrochemical impedance spectroscopy results demonstrate that the surface micropore resistance R_po is 592.4Ω·cm² and the charge transfer resistance is 20840.0Ω·cm², respectively, which endows the material with favorable corrosion resistance. The average iron loss of grain-oriented silicon steel sheet is reduced by approximately 12.28% under the protection of the low-chromium insulating coating, which is comparable to that of the reference chromium coating.

The influence of cold rolling reduction rate on the micro-structure and texture of non-oriented silicon steel with 3.3%Si was studied in this paper. The results show that: the cold-rolled sheet micro-structures under different cold rolling reduction rates all contain a large number of shear band structures and strip-like fiber structures along the rolling direction. The texture is mainly composed of a strong α fiber texture dominated by the rotated cube texture {001}〈100〉 and a very weak γ fiber texture. As the cold rolling reduction rate increases from 84.6% to 88.6%, the shear band structures in the cold-rolled sheet gradually disappear, and the broken and elongated grains gradually form more and more strip-like fiber structures along the rolling direction. The texture continuously changes from the main orientation {110}〈110〉 of the shear band structures to the main orientations {111}〈110〉 and {112}〈111〉 of the strip-like fiber structures. In the finished annealed state, the unfavorable γ texture components gradually strengthen. The intensities of the {111}〈112〉 and {111}〈110〉 textures increase from 1 and 4 to 4 and 8 respectively, showing a four-fold increase. The high-frequency core loss P_1.0/400 of the product decreases from 14.35 W/kg to 12.4 W/kg, while the magnetic induction B₅₀ decreases from 1.687 T to 1.665 T.

To meet the stringent requirements for high surface quality and flatness in the finishing process of grain-oriented silicon steel, and to address the issue of surface damage caused by traditional contact profilometers, this paper proposed a non-contact online flatness detection method based on 3D line laser scanning. In accordance with silicon steel flatness control standards, the system achieves real-time reconstruction of the full-width 3D topography by employing encoder-synchronized triggering, Gaussian noise reduction, point cloud tilt correction, and dual-sensor image fusion. Furthermore, a convolutional neural network (CNN) is utilized to realize the automatic classification and localization of typical defects, such as edge waves and buckles. The system has been successfully applied to the flatness control line of a silicon steel plant. It achieves an identification accuracy of over 95% for typical flatness defects, effectively avoiding the damage to the insulating coating and surface quality associated with contact measurement. By generating intelligent shearing strategies based on the defect distribution of the entire coil, the system guided precise shearing in downstream processes, reducing the flatness concession rate from 17.32% to 8.67%. This significantly improves the yield rate and the level of intelligent production for silicon steel.

Indentation defects (tongue marks) easily occur on the lower surface at the head during coiling of hot-rolled silicon steel coils, which are mostly distributed within 2～8m of the strip head, causing surface quality degradation, head scrapping and reduced yield. Combined with the coiling process characteristics of hot-rolled silicon steel, the formation mechanism of indentation was analyzed throughout the processes of head biting, multi-layer overlapping extrusion and stress solidification. The main inducing factors were clarified from strip head shape, equipment parameters, process system and roller stepping control. A complete set of prevention measures were proposed from process optimization, equipment adjustment, intelligent control and system matching. Field application shows that the defect rate decreases from 18.3% to 2.1% and the yield increases by 1.6% after optimization, which can provide engineering reference for stable coiling quality control of hot-rolled silicon steel.

With the speeding-up of electrical steel production lines, the Tenova horizontal shear presents prominent problems such as cutter box displacement, cumbersome blade replacement, difficult hoisting and potential safety hazards under high-frequency shearing conditions. Based on mechanism analysis, three improvement measures are adopted: installing anti-displacement limit device, optimizing integrated hydraulic release system, and designing special guide mechanism for cutter box replacement. Field application shows that the cutter box displacement fault is completely eliminated, and the shearing qualification rate of wide plate increases from 92% to 99.8%. The blade replacement efficiency is improved by 70%, and the hydraulic failure rate is greatly reduced. The number of operators is reduced from 4 to 1～2 persons, and the operation time is shortened by more than 50%, eliminating hoisting safety risks thoroughly. The optimization features low cost and convenient implementation, which can provide reference for function upgrading and efficiency improvement of horizontal shear in electrical steel production lines.

Aiming at the problems of edge blocking, edge running, chipping, and poor edge trimming quality during high-speed shearing by the rotary shear on the electrical steel normalizing and pickling line, this paper systematically analyzed the equipment mechanism and failure causes. Through measures such as the improvement of the knife box structure, the upgrade of the steering system, parameter optimization, and the standardization of operation and maintenance, the stability of the rotary shear has been significantly improved. This scheme can provide a reference for the stable shearing of rotary shears in similar electrical steel production lines.

With the rapid development of new energy vehicles and high-efficiency industrial motors, higher requirements are put forward for magnetic properties of motor stator cores. Traditional magnetic test of raw electrical steel cannot characterize the influence of processing stress such as stamping, welding and riveting residual stress, as well as actual operating conditions on core magnetic loss. In this paper, an integrated magnetic measurement system for stator core composed of harmonic power supply, magnetic measuring device, power analyzer and special acquisition software is built. The system composition and principles of precise excitation, parameter adjustment and real-time acquisition control are described. New magnetic measurement methods are formed by introducing multi-physical field coupling, multi-sensor fusion and automatic process optimization. Engineering application shows that the system can accurately detect core iron loss and magnetization under different sizes, frequencies and magnetic flux densities. It plays an important supporting role in motor design and material selection, manufacturing process optimization and electrical steel research, and provides practical basis and technical reference for electrical steel application and motor performance improvement.