English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Pro

Presents the zaia usage as premium feature

ZAIA

Presents AI Discovery search usage as a premium feature

AI Discovery

Presents AI Discovery explain and summary usage as a premium feature

Content Analysis

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Presents the pdf analysis as premium feature

PDF Analysis

1500 Top-up

3000 Top-up

Zendy Basic

2500 Top-up

Zendy Unlimited

Presents the access of premium content as premium feature

Premium Content

Recently, not only automatic welders have replaced human welders in many welding applications, but also reasonable seam tracking systems are commercially available. However, fully adequate process control systems have not been developed due to a lack of reliable sensors and mathematical models that correlate welding parameters to the bead geometry for the automated welding process. In this paper, two on-line empirical models using multiple regression analysis are proposed in order to be applicable for the prediction of bead height as welding quality for automatic GMA (Gas Metal Arc) welding process. For development of the proposed models, an attempt has been made to apply for a several methods. For the more accurate prediction, the predicted variables are first used to the surface temperatures measured using infrared thermometers with the welding parameters (welding current, arc voltage) because the surface temperature are strongly related to the formation of the bead geometry. And the developed models are applied for prediction of bead height as welding quality.

On-Line Model to Control Bead Height for Automatic GMA Welding Process