A prediction method of plate convexity based on kernel partial least squares combined with support vector machine

A technology of nuclear partial least squares and support vector machines, which is applied to length measuring devices, contour control, manufacturing tools, etc., can solve problems such as insufficient precision, and achieve the effect of improving prediction accuracy

Active Publication Date: 2021-11-12
TAIYUAN UNIVERSITY OF SCIENCE AND TECHNOLOGY
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Problems solved by technology

[0003] Aiming at the technical problem of insufficient accuracy of the above-mentioned general flatness control method, the present invention provides a rolling strip convexity prediction method based on kernel partial least square method combined with support vector machine, which is simple to operate, easy to implement and high in precision.

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  • A prediction method of plate convexity based on kernel partial least squares combined with support vector machine
  • A prediction method of plate convexity based on kernel partial least squares combined with support vector machine
  • A prediction method of plate convexity based on kernel partial least squares combined with support vector machine

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[0075] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0076] A board convexity prediction method based on kernel partial least squares combined with support vector machine, such as figure 1 shown, including the following steps:

[0077] S1, such as image 3 As shown, the rolling driven plate in the seven-stand continuous rolling production line passes through the roughing mill 1, the flying shear 2, the finishing mill 3, the laminar flow cooling 4, and the coiler 5 in sequence, and collects a large amount of on-...

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Abstract

The invention belongs to the technical field of convexity prediction, and in particular relates to a board convexity prediction method based on kernel partial least squares combined with a support vector machine, comprising the following steps: S1, using a high-precision monitoring device to collect on-site data; S2, collecting the collected Data preprocessing; S3, establishment of KPLS regression prediction model; S4, establishment of KPLS-SVM plate convexity prediction model. In the present invention, the data-driven algorithm is used as a mathematical tool, and abnormal values ​​can be removed from a large amount of collected on-site rolling process data. The present invention establishes a continuous strip rolling strip convexity prediction model based on the kernel-partial least squares method combined with the support vector machine, The prediction of the crown of the strip continuous rolling is realized, and the invention adopts the particle swarm optimization algorithm to optimize the built model, and further improves the prediction accuracy of the strip continuous rolling crown. The invention is used for the prediction of the crown of the continuous rolling strip.

Description

technical field [0001] The invention belongs to the technical field of convexity prediction, and in particular relates to a board convexity prediction method based on kernel partial least squares combined with a support vector machine. Background technique [0002] The plate shape refers to the appearance shape of the plate and strip, which is one of the important indicators to measure the geometric accuracy of the plate and strip, just like the thickness and width. The plate shape actually includes two aspects: the geometric shape of the strip steel section and the flatness of the strip in the natural state. Therefore, quantitative description of the plate shape involves multiple indicators such as convexity, wedge shape, edge weakening, local high point and flatness. , where the plate crown is the main factor to describe and measure the hot-rolled plate shape. The problem of flatness quality has always been the focus of researchers. With the increasing requirements for fl...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): B21B37/28B21B38/02
CPCB21B37/28B21B38/02
Inventor 姬亚锋王晓军宋乐宝彭文李华英原浩牛晶
Owner TAIYUAN UNIVERSITY OF SCIENCE AND TECHNOLOGY
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