Development of the Intelligent Grinding Workstation for the Welds at the Pipe Ends of Robots

LI Hongtao; QIN Weitao; FU Ao; ZHOU Kun; BAI Shuo; ZHANG Qing; WANG Yueyao

doi:10.7512/j.issn.1001-2303.2026.06.16

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Development of the Intelligent Grinding Workstation for the Welds at the Pipe Ends of Robots
Vol. 56, Issue 6, Pages: 129-135(2026)
Received：23 March 2025，

Revised：2025-04-28，

Published：20 June 2026
DOI： 10.7512/j.issn.1001-2303.2026.06.16
稿件说明：

移动端阅览

李洪涛，秦伟涛，付傲，等.机器人管端焊缝智能打磨工作站研制［J］.电焊机，2026，56（6）：129-135. DOI： 10.7512/j.issn.1001-2303.2026.06.16.

LI Hongtao, QIN Weitao, FU Ao, et al.Development of the Intelligent Grinding Workstation for the Welds at the Pipe Ends of Robots[J].Electric Welding Machine, 2026, 56(6): 129-135. DOI： 10.7512/j.issn.1001-2303.2026.06.16.

摘要

针对管端焊缝存在的几何复杂性高、多材质适配性差及工艺参数动态优化不足，人工打磨效率低、质量一致性差等问题，以视觉传感器技术为基础，二次开发视觉传感器在打磨中的控制技术，研制了一种融合多源传感与智能决策的机器人智能打磨工作站。工作站集成三维结构光束视觉传感器与激光位移测距传感器，构建多模态感知系统：通过结构光条纹投影实现焊缝形貌的亚毫米级三维重建（点云密度≥2 000点/cm

），结合激光测距数据补偿钢管椭圆度误差（补偿精度±0.05 mm），综合检测精度提升至0.1 mm（较单传感器方案提升60%）。解决了复杂曲面自适应跟踪难题；提出二次寻位的程序运算轨迹算法，将轨迹跟踪精度提升至±0.08 mm。研究突破了多源信息融合、工艺知识库构建等关键技术，为管道制造行业智能化升级提供了理论支撑与装备范式。

Abstract

To address the high geometric complexity

poor multi-material adaptability

and insufficient dynamic optimization of process parameters in end weld seams

as well as the low efficiency and poor quality consistency of manual grinding

a rob

otic intelligent grinding workstation was developed based on visual sensor technology. This workstation integrates a three-dimensional structured light beam vision sensor and a laser displacement distance sensor to create a multimodal perception system. It achieves sub-millimeter-level three-dimensional reconstruction of weld seam morphology using structured light stripe projection (point cloud density ≥ 2 000 points/cm

) and compensates for pipe ellipticity errors with laser distance data (compensation accuracy ±0.05 mm)

thereby improving the overall detection accuracy to 0.1 mm (a 60% improvement over single-sensor solutions). It solves the problem of adaptive tracking of complex surfaces; a secondary positioning trajectory algorithm was proposed

which enhances trajectory tracking accuracy to ±0.08 mm. The research has overcome key technologies such as multi-source information fusion and the construction of a process knowledge base

providing theoretical support and equipment paradigms for the intelligent upgrade of the pipeline manufacturing industry. It realizes intelligent recognition

precise tracking

and grinding of weld seams.

关键词

Keywords

references

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