Research on a visual weld detection method based on invariant moment features

Zeng Jinle (Key Laboratory for Advanced Materials Processing Technology, Ministry of Education, Tsinghua University, Beijing, China)
Zou Yirong (Key Laboratory for Advanced Materials Processing Technology, Ministry of Education, Tsinghua University, Beijing, China)
Du Dong (Key Laboratory for Advanced Materials Processing Technology, Ministry of Education, Tsinghua University, Beijing, China)
Chang Baohua (Key Laboratory for Advanced Materials Processing Technology, Ministry of Education, Tsinghua University, Beijing, China)
Pan Jiluan (Key Laboratory for Advanced Materials Processing Technology, Ministry of Education, Tsinghua University, Beijing, China)

Industrial Robot

ISSN: 0143-991x

Publication date: 16 March 2015

Abstract

Purpose

This paper aims to develop a feasible visual weld detection method to solve the problems in multi-layer welding detection (e.g. cover pass welding detection) for seam tracking and non-destructive testing. It seeks for an adaptive and accurate way to determine the edge between the seam and the base metal in the grayscale image of weld automatically. This paper tries to contribute to next-generation real-time robotic welding systems for multi-layer welding.

Design/methodology/approach

This paper opted for invariant moments to characterize the seam and the base metal for classification purposes. The properties of invariant moments, such as high degree of self-similarity and separation, affine invariance and repetition invariance, were discussed to verify the adaptability of the invariant moment in weld detection. Then, a weld detection method based on invariant moments was proposed to extract the edge between the seam and the base metal, including image division, invariant moment features extraction, K-Means adaptive thresholding, maximum connected domain detection and edge position extraction.

Findings

This paper highlights the significance of high degree of self-similarity and separation, affine invariance and repetition invariance of the invariant moment for weld detection. An adaptive, effective and accurate method is proposed to detect the edge between the seam and the base metal based on invariant moments.

Research limitations/implications

It is necessary to verify the applicability of the proposed method in variable welding conditions further. Further works will focus on the establishment of a real-time seam tracking system during the whole multi-layer/multi-pass welding process based on such adaptive visual features.

Practical implications

This paper includes the implications for development of an adaptive and real-time weld detection method, which is expected to be applied to online seam tracking in multi-layer welding.

Originality/value

This paper presents an accurate weld detection method in multi-layer welding, overcoming difficulties in effectiveness, adaptability and efficiency of existing weld detection methods.

Keywords

Acknowledgements

This work is supported by the National Natural Science Foundation of China under Grant Number 51375257.

Citation

Jinle, Z., Yirong, Z., Dong, D., Baohua, C. and Jiluan, P. (2015), "Research on a visual weld detection method based on invariant moment features", Industrial Robot, Vol. 42 No. 2, pp. 117-128. https://doi.org/10.1108/IR-06-2014-0358

Publisher

:

Emerald Group Publishing Limited

Copyright © 2015, Emerald Group Publishing Limited

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