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A welding seam identification method based on cross-modal perception

journal contribution
posted on 2020-03-04, 00:00 authored by X Li, P Li, Mohammad KhyamMohammad Khyam, X He, SS Ge
Purpose: As an automatic welding process may experience some disturbances caused by, for example, splashes and/or welding fumes, misalignments/poor positioning, thermally induced deformations, strong arc lights and diversified welding joints/grooves, precisely identifying the welding seam has a great influence on the welding quality. This paper aims to propose a robust method for identifying this seam based on cross-modal perception. Design/methodology/approach: First, after a welding image obtained from a structured-light vision sensor (here laser and vision are integrated into a cross-modal perception sensor) is filtered, in a sufficiently small area, the extended Kalman filter is used to prevent possible disturbances to search for its laser stripe. Second, to realize the extraction of the profile of welding seam, the least square method is used to fit a sequence of centroids determined by the scanning result of columns displayed on the tracking window. Third, this profile is then qualitatively described and matched using a proposed character string method. Findings: It is demonstrated that it maintains real time and is clearly superior in terms of accuracy and robustness, though its real-time performance is not the best. Originality/value: This paper proposes a robust method for automatically identifying and tracking a welding seam.

History

Volume

46

Issue

3

Start Page

453

End Page

459

Number of Pages

7

eISSN

1758-5791

ISSN

0143-991X

Publisher

Emerald Publishing, UK

Peer Reviewed

  • Yes

Open Access

  • No

Acceptance Date

2018-11-06

External Author Affiliations

National University of Singapore, Singapore; Southeast University, Nanjing, China;

Era Eligible

  • Yes

Journal

Industrial Robot: An International Journal