Method for analyzing influences of grain sizes on magnetic performance of non-oriented silicon steel on basis of principal components regression analysis

A principal component regression, oriented silicon steel technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problem of revealing the relationship between grains of different sizes and the magnetic properties of non-oriented silicon steel, which is rare, etc.

Active Publication Date: 2014-03-12
UNIV OF SCI & TECH BEIJING
View PDF3 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] At present, there have been a lot of researches on the influence of grain size on the magnetic properties of non-oriented silicon steel at home and abroad, but the relationship between grain size and magnetic properties has only been examined qualitatively from the aspects of average grain s...

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Method for analyzing influences of grain sizes on magnetic performance of non-oriented silicon steel on basis of principal components regression analysis
  • Method for analyzing influences of grain sizes on magnetic performance of non-oriented silicon steel on basis of principal components regression analysis
  • Method for analyzing influences of grain sizes on magnetic performance of non-oriented silicon steel on basis of principal components regression analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0034] The present invention will be further explained and illustrated below in conjunction with the embodiments and accompanying drawings.

[0035] The embodiment adopts the non-oriented silicon steel product test samples 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 groups of magnetic properties. Different samples were studied, and the magnetic properties of each group of samples are shown in Table 2.

[0036] The magnetic property of table 2 embodiment sample

[0037]

[0038]

[0039] Use the EBSD system of ZEISSULTRA55 field emission scanning electron microscope and Channel5 orientation analysis software to measure the content of grains in different size ranges of statistical samples. The observation surface of the sample is divided into rolled surface and longitudinal section, at 100 to 200 times, preferably 100 times the field of view In this ca...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to a method for analyzing the influences of grain sizes on the magnetic performance of non-oriented silicon steel on the basis of principal component regression analysis. The method comprises the following steps: measuring the content of grains with different size ranges in the non-oriented silicon steel; standardizing all data; performing dimension reduction on the content data of the grains with different size ranges; calculating a characteristic value and determining a principal component and an expression thereof; performing regression analysis and performing significance testing on a regression equation; and converting the regression equation into a multivariate linear relation between the contents of grains with different size ranges and the magnetic performance of the non-oriented silicon steel by using inverse operation of a standard difference standardization method. According to the method, a multivariable program can be analyzed effectively, and the multivariate linear relation among variables is analyzed quantitatively by acquiring major information from complicated influence factors so as to quantitatively reflect the rule of the influences of the contents of grains with different size ranges on the magnetic performance of the non-oriented silicon steel, so that oriented guidance is provided for the practical production of efficient electrical steel products with low iron losses and high magnetic induction.

Description

technical field [0001] The invention belongs to the technical field of performance control of non-oriented silicon steel, and in particular relates to an analysis method based on principal component regression analysis of the influence of grain size on the magnetic properties of non-oriented silicon steel. Background technique [0002] With the rapid development of electric power, telecommunications and other industries, all kinds of generators, motors, compressors and other products are required to be high-efficiency, high-precision, and miniaturized to meet the standards of energy saving and environmental protection. Non-oriented silicon steel is an important material for manufacturing these products. Materials are increasingly required to have excellent magnetic properties with lower iron loss and high magnetic induction. Relevant studies have shown that grain size is the main factor affecting the loss of non-oriented silicon steel. Analyzing the influence of grain conten...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F17/50
Inventor 赵志毅陈凌峰王宝明黄赛闻强苗李平潮薛润东
Owner UNIV OF SCI & TECH BEIJING
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap