Research on machine vision size measurement method based on particle weight

Bao, Nengsheng; Wu, Zhanfu; Ran, Xie; Wang, Keyan; Xue, Yusheng

doi:10.1109/itnec.2017.8285045

Cited by 3 publications

(2 citation statements)

References 2 publications

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“…Structured light vision measurement technology, which operates based on the principle of laser triangulation, offers a non-contact optical measurement solution. This technology enables fast and efficient measurement of relevant dimensions without touching the workpiece surface [ 8 , 9 , 10 , 11 ]. Projection of a structured light pattern onto the surface of the workpiece and capturing the structured light image using a calibrated industrial camera makes it possible to rapidly calculate the actual three-dimensional information of the surface using the camera imaging model [ 12 , 13 , 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

A Method for Measuring Shaft Diameter Based on Light Stripe Image Enhancement

Li,

Xu,

Liu

et al. 2024

Sensors

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When the workpiece surface exhibits strong reflectivity, it becomes challenging to obtain accurate key measurements using non-contact, visual measurement techniques due to poor image quality. In this paper, we propose a high-precision measurement method shaft diameter based on an enhanced quality stripe image. By capturing two stripe images with different exposure times, we leverage their different characteristics. The results extracted from the low-exposure image are used to perform grayscale correction on the high-exposure image, improving the distribution of stripe grayscale and resulting in more accurate extraction results for the center points. The incorporation of different measurement positions and angles further enhanced measurement precision and robustness. Additionally, ellipse fitting is employed to derive shaft diameter. This method was applied to the profiles of different cross-sections and angles within the same shaft segment. To reduce the shape error of the shaft measurement, the average of these measurements was taken as the estimate of the average diameter for the shaft segment. In the experiments, the average shaft diameters determined by averaging elliptical estimations were compared with shaft diameters obtained using a coordinate measuring machine (CMM) the maximum error and the minimum error were respectively 18 μm and 7 μm; the average error was 11 μm; and the root mean squared error of the multiple measurement results was 10.98 μm. The measurement accuracy achieved is six times higher than that obtained from the unprocessed stripe images.

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Section: Introductionmentioning

confidence: 99%

A Method for Measuring Shaft Diameter Based on Light Stripe Image Enhancement

Li,

Xu,

Liu

et al. 2024

Sensors

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“…Shen et al [10] proposed a sub-pixel repositioning method based on local area grayscale to measure the thickness of the cable sheath cone by extracting edge contours for segmentation after image pre-processing, and then using the sub-pixel repositioning method with local area grayscale to achieve the parameter measurement. From the above studies, it can be seen that most of the cable parameter measurement algorithms based on machine vision are 2D vision techniques, and most of these image processing methods extract the edges of the corresponding features by linear mapping of the object [11]. Since there is no significant change in the gray value information at the junction of multiple regions on the cable joint, errors are easily generated in the edge extraction, making it difficult to meet the measurement requirements of the cable joints including anti-stress cone with these existing non-contact parameter measurement methods.…”

Section: Introductionmentioning

confidence: 99%

Dimensional measurement of anti-stress cone of HV cable joints based on 3D point cloud

Zheng

Gao

et al. 2023

Meas. Sci. Technol.

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To solve the problem of automatic measurement of anti-stress cone of HV(high voltage) cable joints, a measurement algorithm based on 3D point cloud is proposed. Firstly, denoising and coordinate adjustment of point cloud of a cable joint are realized. Then the characteristic curve model of fitting circle radius indicating structure characteristic of cable joints is constructed by fitting circles with RANSAC algorithm . After that, the discrete points on the characteristic curve are extracted according to the characteristics such as the fluctuation range of the characteristic curve for straight line fitting and the intersection of the fitted lines is calculated to complete the segmentation of the anti-stress cone area of the cable joint. Finally, the parameter measurement of the anti-stress cone was completed according to the structure of the anti-stress cone, and the error correction post-processing was performed. Two types of cable joint point clouds with standard dimensions and surface defects were used for measurement experiments, the absolute errors of the measurement results are less than 0.2mm and 1.0mm respectively, and the relative errors are less than 0.25% and 2% respectively, indicating that the proposed method has high robustness and measurement accuracy,which meet the measurement requirements in engineering practice.

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