IPCA-SVM based real-time wrinkling detection approaches for strip steel production process
by Tong Zhao; Xiong Chen; Lirong Yang
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 16, No. 2, 2019

Abstract: Strip steel wrinkling is one of the common problems in strip steel production line. The wrinkling phenomenon has a serious impact on the quality of the products, resulting in product waste, and even leading to the entire production line downtime. The key point to solve the problem is real-time detection for strip wrinkling while making an early warning. This paper proposes an IPCA-SVM based online wrinkling detection approach. IPCA is used to compress each frame image from industrial camera and extract effective features from frame images. The projection coefficients of each frame image on the principal components are the inputs to SVM model for classification. Experiment results show that the proposed method is valid for real-time wrinkling detection for strip steel production process.

Online publication date: Fri, 12-Apr-2019

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Wireless and Mobile Computing (IJWMC):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com