When the thin slab caster produces low-carbon steel, the uneven cooling alarm can easily occur at both sides of the nozzle in the thermal image, and there are cracks at the corresponding positions where the uneven cooling occurs. The causes of uneven cooling are studied, and the mechanism of uneven cooling causing surface cracks is proposed. The results show that the generation of uneven cooling is greatly related to the carbon content of molten steel, the thickness of the copper plate, and the hydrogen content. The surface roughness method shows that the uneven cooling index increases with the increase of carbon content. The uneven cooling index gradually increases with the decrease of the copper plate thickness. When the copper plate thickness is less than 41 mm, the uneven cooling index of the mold increases from the 1.1 to about 14.7. With the increase of H content, the uneven cooling index increases. When H exceeds 7 ppm, the uneven cooling index can reach 14.5. By adopting reasonable and effective control measures, the uneven cooling index of the mold is significantly reduced from 3.85 to 0.73, and the surface crack defects in multi-mode continuous casting-rolling line are effectively alleviated.
We propose a DSP-based algorithm for monitoring PSP trajectories and rotation speeds. By using sliding-window median-filtering and modulus judgment method, the algorithm can precisely recover the PSP trajectories and determine the rotation speeds more accurately.
Hyperspectral images (HSIs) have hundreds of narrow and adjacent spectral bands, which will result in feature redundancy, decreasing the classification accuracy. Feature (band) selection helps to remove the noisy or redundant features. Most traditional feature selection algorithms can be only performed on a single HSI scene. However, appearance of massive HSIs has placed a need for joint feature selection across different HSI scenes. Cross-scene feature selection is not a simple problem, since spectral shift exists between different HSI scenes, even though the scenes are captured by the same sensor. The spectral shift makes traditional single-dataset-based feature selection algorithms no longer applicable. To solve this problem, we extend the traditional ReliefF to a cross-domain version, namely, cross-domain ReliefF (CDRF). The proposed method can make full use of both source and target domains and increase the similarity of samples belonging to the same class in both domains. In the cross-scene classification problem, it is necessary to consider the class-separability of spectral features and the consistency of features between different scenes. The CDRF takes into account these two factors using a cross-domain updating rule of the feature weights. Experimental results on two cross-scene HSI datasets show the superiority of the proposed CDRF in cross-scene feature selection problems.
In the current study, the movement of the vortex center position and the prediction of the maximum velocity at the top surface with different casting parameters were studied in a steel continuous casting slab strand using the Eulerian–Eulerian approach. One, two, and three vortexes were generated under the flow pattern of single roll flow, double roll flow, and complex roll flow, respectively. The vortex center position migrated from the meniscus to the submerged entry nozzle in the upper recirculation zone and moved downward along the mold height in the lower recirculation zone with the increasing of the casting speed, respectively. With the increasing of the argon flow rate, the movement trajectory of vortex center was opposite to the increasing of the casting speed. The vortex center position moved from the meniscus to the submerged entry nozzle with the outport angle of submerged entry nozzle increased and migrated from the submerged entry nozzle to the meniscus with mold width increased. In addition, nonlinear fitting for the maximum velocity of the molten steel at the top surface under different cast parameters was performed, and the regression equation was verified by nail board measurements The on-line prediction of the maximum velocity at the top surface was realized.
The flow control devices (FCDs) in the tundish play an important role in steel cleanliness and removal of macro-inclusions. To eliminate the spot-like defects during deep-drawing process, the liquid steel samples were taken from tundish in three industrial IF steel heats, and the effect of weir structure in the tundish on the steel cleanliness were evaluated and compared with the aid of ASPEX with the total detection area of over 54 000 mm 2 . The results showed that non-metallic inclusions over 5 µm observed in the liquid tundish samples were categorized into two types: type 1: alumina based inclusions and type 2: calcium aluminates. Compared to the tundish without weir, the number density of macro-inclusions reduces by half when furnished with weir. In addition, several large sized calcium aluminates were occasionally found without weir whereas no calcium aluminates were detected with the weir. The mechanism of the inclusion distributions with the weir was proposed based on the experimental results, which shows that the weir act as a baffle that block the large sized inclusions from moving toward the mould. After using the weir in the actual casting practice, the occurrence ratio of spot-like defects was decreased by about 25%.
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