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Online cold-rolled steel strip shape statistic method

A cold-rolled strip, statistical method technology, applied in the direction of calculation, special data processing applications, instruments, etc., can solve the problems of inaccurate statistical results of the fluctuating critical shape value, achieve reduced losses, improve hit rate, The effect of improving accuracy

Inactive Publication Date: 2013-10-30
YANSHAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The binning percentage method is too clear for each shape value interval, and the statistical results of the fluctuating critical shape value are not accurate enough

Method used

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  • Online cold-rolled steel strip shape statistic method
  • Online cold-rolled steel strip shape statistic method
  • Online cold-rolled steel strip shape statistic method

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Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0045] Below in conjunction with accompanying drawing and specific embodiment the present invention is described in further detail:

[0046] Figure 1 to Figure 4 It is the calculation flow chart of the flatness on-line statistical method of the present invention. Taking the online detection data of one coil of strip steel of a certain 1050 rolling mill as an example, an online flatness statistical model of cold-rolled strip is established. Collect the plate shape data of the sixth pass, the entrance thickness is 0.42mm, the exit thickness is 0.29mm, and the width is 910mm.

[0047] First, set the macro shape grade level, the list is as follows:

[0048] Shape grade

Class I

Class II

Class III

Class IV

Class V

Level VI

Set critical shape value

≤4I

≤6I

≤8I

≤12I

≤16I

≤20I

Statistical probability of macro flat shape

[0049] Then, set the critical flatness value of e...

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Abstract

The invention relates to an online cold-rolled steel strip shape statistic method which mainly includes macroscopic shape data statistics, shape component data statistics and shape data distribution test and fuzzing. By the aid of two present frequently-used shape statistic methods including a statistic method based on a probability theory and a grading percent statistic method, distribution laws that shape data comply with are tested by a K-S (Kolmogorov-Smirnov) test method and a chi-square test method in a goodness-of-fit test theory, critical shape values are fuzzed by a fuzzy theory method, and finally, macroscopic shape statistics is realized. Shape components are recognized by the aid of a pattern recognition theory, shape component data distribution is tested, shape component data are fuzzed, and shape component statistics is finished. The online cold-rolled steel strip shape statistic method has a strict mathematical theory basis, and reliable shape statistics data are provided for production of high-performance cold-rolled steel strips by combining the shape theory with the probability statistics theory.

Description

technical field [0001] The invention relates to a statistical technology of flatness quality in the cold rolling process of strips, in particular to an online flatness statistical method for cold-rolled strips based on goodness-of-fit test theory, fuzzy mathematics theory and pattern recognition theory. Background technique [0002] Shape is an important index to measure the grade of cold-rolled strip products, and the shape problem has always been one of the on-site problems that plague iron and steel enterprises. In the production process, under the large front and rear tension of cold-rolled strip steel, online shape defects are often hidden, and their magnitudes are extremely small (10 -5 ), it is difficult to measure, and it is difficult to quantitatively evaluate and finely control the strip shape based on experience alone, resulting in poor shape stability of the entire strip in the entire length range, and the strip after uncoiling or annealing tends to show various ...

Claims

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Application Information

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IPC IPC(8): G06F19/24
Inventor 杨利坡丁顺风于丙强朱建旭
Owner YANSHAN UNIV
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