Flatness prediction model based on wavelet transform

Author

Jin, Wuming ; Wang, Jinkuan ; Zhao, Qiang ; Han, Yinghua

Author_Institution

Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China

Volume

4

fYear

2010

fDate

25-27 June 2010

Abstract

Flatness prediction model is one of the important techniques in flatness control system of high precision. In this paper, the nonlinear wavelet denoising method is used to filter the noise of the measure data availably. Then the filtered data are applied to recognize the flatness through the model based on multiple linear regression. The prediction model of symmetrical and asymmetrical coefficients can be obtained. The combination of wavelet transform and multiple linear regression can improve precision. The simulation results exhibit the effectiveness of our method.

Keywords

cold rolling; filtering theory; regression analysis; steel; wavelet transforms; asymmetrical coefficients; cold rolling; flatness control system; flatness prediction model; linear regression; noise filtering; nonlinear wavelet denoising method; steel strip; wavelet transform; Automatic control; Discrete wavelet transforms; Linear regression; Milling machines; Noise reduction; Predictive models; Signal resolution; Strips; Time measurement; Wavelet transforms; flatness coefficients; multiple linear regression; wavelet transform denoise;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Design and Applications (ICCDA), 2010 International Conference on

Conference_Location

Qinhuangdao

Print_ISBN

978-1-4244-7164-5

Electronic_ISBN

978-1-4244-7164-5

Type

conf

DOI

10.1109/ICCDA.2010.5541063

Filename

5541063