Systematic Error Correction in Robotic-OCT Inspection of Hard-to-Reach Industrial Parts

Hard-to-reach industrial parts have complex geometries, such as internal holes and deep cavities, posing challenges for accurate 3-D measurement. Robotic-arm-assisted optical coherence tomography (robotic-OCT) is a promising method for its ability to access hard-to-reach spaces with a compact probe, high resolution, and flexibility. However, probe misalignment and nonuniform rotation in robotic-OCT systems introduce systematic errors and sacrifice measurement accuracy. In this article, we report a technique for achieving precise self-alignment between the OCT probe and workpiece by utilizing the data feedback mechanism inherent in OCT scanning. We also propose a nonuniform rotational distortion correction method to rectify distortion errors. Experimental results showed that the proposed method improved point cloud completeness to 98.7%, surpassing uncorrected (77.6% ) and manual correction (96.8% ), and reduced errors by 84.1% compared to uncorrected and 13.0% compared to manual correction, while greatly enhancing efficiency over manual correction. The robotic-OCT system, with reduced errors, achieved a measurement accuracy better than 4.5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\boldsymbol {\mu }$</tex-math></inline-formula>m for internal holes with diameters from 5 to 100 mm.

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Journal
IEEE/ASME Transactions on Mechatronics
Published
2025-01-01
DOI
https://doi.org/10.1109/tmech.2025.3602812
Primary Topic
Industrial Vision Systems and Defect Detection
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article
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article

Systematic Error Correction in Robotic-OCT Inspection of Hard-to-Reach Industrial Parts

Zhongxing Wang, Wangping Xiong, Yu Sun, Jiancai Huang et al.
IEEE/ASME Transactions on Mechatronics
Industrial Vision Systems and Defect Detection
article

Systematic Error Correction in Robotic-OCT Inspection of Hard-to-Reach Industrial Parts

Zhongxing Wang, Wangping Xiong, Yu Sun, Jiancai Huang, Yurui Pu, Xingjian Liu, Xiaolong Yu, R. Zou
article en

Abstract

Hard-to-reach industrial parts have complex geometries, such as internal holes and deep cavities, posing challenges for accurate 3-D measurement. Robotic-arm-assisted optical coherence tomography (robotic-OCT) is a promising method for its ability to access hard-to-reach spaces with a compact probe, high resolution, and flexibility. However, probe misalignment and nonuniform rotation in robotic-OCT systems introduce systematic errors and sacrifice measurement accuracy. In this article, we report a technique for achieving precise self-alignment between the OCT probe and workpiece by utilizing the data feedback mechanism inherent in OCT scanning. We also propose a nonuniform rotational distortion correction method to rectify distortion errors. Experimental results showed that the proposed method improved point cloud completeness to 98.7%, surpassing uncorrected (77.6% ) and manual correction (96.8% ), and reduced errors by 84.1% compared to uncorrected and 13.0% compared to manual correction, while greatly enhancing efficiency over manual correction. The robotic-OCT system, with reduced errors, achieved a measurement accuracy better than 4.5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\boldsymbol {\mu }$</tex-math></inline-formula>m for internal holes with diameters from 5 to 100 mm.

IEEE/ASME Transactions on Mechatronics
University of Toronto (CA), Dalian University of Technology (CN)
Openalex Percentile: Top 65%
Industrial Vision Systems and Defect Detection
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Systematic Error Correction in Robotic-OCT Inspection of Hard-to-Reach Industrial Parts — Zhongxing Wang, Wangping Xiong, et al. · IEEE/ASME Transactions on Mechatronics (2025) | TGRS Research Map | TGRS