Principal component regression analysis method for analyzing influence of texture components on magnetic induction of non-oriented silicon steel

A principal component regression, oriented silicon steel technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as difficulty in judging the degree of influence, and achieve the effect of simplifying the structure

Active Publication Date: 2014-05-28
UNIV OF SCI & TECH BEIJING
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Problems solved by technology

[0004] However, relevant domestic and foreign studies only qualitatively analyzed the evolution process of texture and its influence on the magnetic properties of non-oriented silicon steel by using ODF diagrams and pole figures, but failed to study the magnetic induction and different textures of non-oriented silicon steel from a quantitative perspective. In addition, there are basically no scholars at home and abroad using mathematical methods to analyze the influence of texture on the magnetic induction of non-oriented silicon steel. It is difficult to judge the texture components that significantly affect the magnetic induction and the effects of different texture components on the magnetic induction. influence level

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  • Principal component regression analysis method for analyzing influence of texture components on magnetic induction of non-oriented silicon steel
  • Principal component regression analysis method for analyzing influence of texture components on magnetic induction of non-oriented silicon steel
  • Principal component regression analysis method for analyzing influence of texture components on magnetic induction of non-oriented silicon steel

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Embodiment Construction

[0040] The present invention will be further explained and illustrated below in conjunction with the embodiments and accompanying drawings.

[0041] The embodiment adopts the non-oriented silicon steel 50SW1300 finished product test sample provided by a steel factory after continuous casting, hot rolling (2.6mm thick), cold rolling (0.5mm thick), continuous annealing and surface coating, and selects 10 sets of magnetic induction Different samples were studied, and the magnetic induction of each group of samples is shown in Table 2.

[0042] The magnetic induction of table 2 embodiment sample

[0043]

[0044] Use the EBSD system of ZEISS ULTRA55 field emission scanning electron microscope and Channel5 orientation analysis software to measure the different texture content of the sample. The observation surface of the sample is divided into rolling surface and longitudinal section. Scanning under 100-500 times, preferably 100 times field of view The step length is selected a...

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Abstract

The invention relates to a principal component regression analysis method for analyzing influence of texture components on magnetic induction of non-oriented silicon steel. The principal component regression analysis method comprises the steps of measuring contents of different texture components in the non-oriented silicon steel; performing standardized processing on all the data; performing dimension reduction processing on statistical data; calculating a characteristic value, and determining quantities of principal components and expressions of the principal components; performing regression analysis, and performing significance testing on a regression equation; if the regression equation has non-significant independent variables, performing significance testing on the independent variables; transforming the regression equation into a multivariate linear equation of magnetic induction about the contents of different texture components through inverse operation of a standard deviation standardization method. By means of the principal component regression analysis method, the multivariable problem can be analyzed effectively, multiple correlated variables can participate in operation with the same weight, quantitative research on the rule of influence of different texture components on magnetic induction of non-oriented silicon steel can be performed, texture components obviously significant in magnetic induction can be found out, and directional guidance is provided for actually producing non-oriented silicon steel products with excellent magnetic property.

Description

technical field [0001] The invention relates to the technical field of controlling the properties of non-oriented silicon steel, in particular to a principal component regression analysis method for the influence of texture components on the magnetic induction of non-oriented silicon steel. Background technique [0002] In recent years, due to the rapid development of electric power, telecommunications and other industries, high efficiency, high precision and miniaturization are the mainstream goals pursued by various motors, generators, compressors and other products, so as to achieve energy saving, consumption reduction and environmental protection. Standard, and cold-rolled non-oriented silicon steel, as an important soft magnetic material widely used in the manufacture of these products, requires excellent magnetic properties: high magnetic induction and low iron loss. [0003] Studies have shown that texture is an important factor affecting the magnetic induction of non...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 赵志毅王宝明陈凌峰闻强苗李平潮黄赛薛润东
Owner UNIV OF SCI & TECH BEIJING
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