Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Principal component regression analysis method of non-oriented silicon steel magnetism performance influence factor

A principal component regression, oriented silicon steel technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problems of rare and difficult to determine magnetic properties and other factors

Active Publication Date: 2014-05-28
UNIV OF SCI & TECH BEIJING
View PDF0 Cites 12 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] At present, there have been a lot of studies on the analysis of inclusions, texture, and grain size in non-oriented silicon steel at home and abroad, but most of them are only from a qualitative point of view, respectively examining their relationship with the magnetic properties of non-oriented silicon steel. However, it is impossible to comprehensively study the influence of inclusions, texture, and grain size on the magnetic properties of non-oriented silicon steel from a quantitative perspective, and it is difficult to determine the factors that significantly affect the magnetic properties. There are few studies on the influence of texture and grain size on the magnetic properties of non-oriented silicon steel

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
  • Principal component regression analysis method of non-oriented silicon steel magnetism performance influence factor
  • Principal component regression analysis method of non-oriented silicon steel magnetism performance influence factor
  • Principal component regression analysis method of non-oriented silicon steel magnetism performance influence factor

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0042] The present invention will be further explained and illustrated below in conjunction with the embodiments and accompanying drawings.

[0043] 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 properties Various samples were studied, and the magnetic properties of each group of samples are shown in Table 2.

[0044] The magnetic property of table 2 embodiment sample

[0045]

[0046] Use ZEISS ULTRA55 field emission scanning electron microscope and energy spectrometer to conduct random continuous observation of inclusions under the field of view of 5000-20000 times, and the statistical points are >1000nm, 500-1000nm, 200-500nm, 100-200nm four size ranges, mainly Study the inclusion content in the size range of 200-500nm and 100-200nm.

[0047] Th...

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 principal component regression analysis method of a non-oriented silicon steel magnetism performance influence factor. According to the method, the content of inclusions in different size intervals of non-oriented silicon steel of the same mark, the content of beneficial and harmful textured components and the content of crystal particles within different size ranges are recorded; standardized processing and dimension reduction processing are carried out on all data; a feature value is calculated, and the number of principal components and expressions of the principal components are determined; regression analysis is carried out, and a significance test is carried out on a regression equation; if a non-significant independent variable exists in the regression equation, the significance test is carried out on the independent variable; the regression equation is converted to a multielement linear relation between the sizes of the inclusions, the textured components and the crystal particles and non-oriented silicon steel magnetism performance by means of inverse operations of a standard deviation standardization method. The rules of influences of the sizes of the inclusions, the textured components and the crystal particles on the non-oriented silicon steel magnetism performance can be comprehensively researched by means of the method, the factor which remarkably influences magnetism performance is found, and directivity guide is provided for production of non-oriented silicon steel products which are high in magnetic induction and low in iron loss in actual production.

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 of factors affecting the magnetic properties of non-oriented silicon steel. Background technique [0002] With the society's increasing attention to energy, environmental protection and other issues and the rapid development of electric power, telecommunications and other industries, various motors, generators, compressors and other products require high efficiency, high precision and miniaturization to achieve energy saving and consumption reduction , environmental protection standards, and cold-rolled non-oriented silicon steel is widely used as an important soft magnetic material required for the manufacture of these products, so the requirements for its performance (especially magnetic properties) are getting higher and higher, and the pursuit of lower Fe Excellent magnetic prope...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 赵志毅王宝明陈凌峰李平潮闻强苗赵东红薛润东
Owner UNIV OF SCI & TECH BEIJING
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products