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A robust weld seam detection method based on particle filter for laser welding by using a passive vision sensor

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Abstract

Vision sensor systems with an auxiliary light source such as structured light–based vision sensor have been widely used for weld seam detection. However, the main drawback of this method is the preview distance between the welding position and the sensing position, which can generate unavoidable detecting errors. Laser welding of the small workpiece or narrow butt joint is especially vulnerable to detection error caused by preview distance. Meanwhile, only one point of the weld seam can be measured each time, which makes the corresponding image processing very sensitive to light noise. Consequently, a seam measurement method based on a passive vision sensor for narrow gap butt joint is proposed in this article. The weld pool is observed directly by this vision sensor so that there is no preview distance. An adequately adjusted telecentric lens is used to increase the contrast between the seam feature and the background welding noise. By this manner, a long and noticeable weld seam feature, as well as the weld pool, can be obtained in the captured images. A corresponding image processing algorithm based on particle filter is designed to extract the captured long weld seam. The particle filter is used to track the slope and intercept of the weld seam, which combines the advantage of both particle filter and Hough transform. As the particle filter algorithm could generate the result by evaluating both the previous and the current measurement results, the corresponding image processing can be robust even when a few images are of poor quality. Finally, laser welding experiments were carried out, and the results revealed that the proposed method could achieve detection accuracy of 0.08 mm when welding 0.1 mm width narrow butt joint at 2000 mm/min welding speed.

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Funding

This research is supported by National Natural Science Foundation of China (51805190), National Basic Research Program of China (973 Program, 2014CB046703), Mega Project of Science Research of Hubei Province (2016AAA070), and the China Postdoctoral Science Foundation (2018M632832).

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Authors and Affiliations

  1. State Key Lab of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China

    WenJun Shao & XiuFeng Liu

  2. National CAD Support Software Engineering Research Center, Huazhong University of Science and Technology, Wuhan, 430074, China

    ZiJun Wu

Authors
  1. WenJun Shao
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  2. XiuFeng Liu
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Correspondence to ZiJun Wu.

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Shao, W., Liu, X. & Wu, Z. A robust weld seam detection method based on particle filter for laser welding by using a passive vision sensor. Int J Adv Manuf Technol 104, 2971–2980 (2019). https://doi.org/10.1007/s00170-019-04029-x

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  • DOI: https://doi.org/10.1007/s00170-019-04029-x

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