Research on the on-line dimensional accuracy measurement method of conical spun workpieces based on machine vision technology

Xiao, Gangfeng; Li, Yong-Ting; Xia, Qinxiang; Cheng, Xuansheng; Chen, Weiping

doi:10.1016/j.measurement.2019.106881

Cited by 48 publications

(21 citation statements)

References 14 publications

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“…Nevertheless, this method is cheap, fast, and the instrumentation (the camera plus the tripod) can be delivered where necessary, if it is needed to monitor many manufacturing processes on the same part. Clearly, this method is only available when dealing with cylindrical or conical pieces [16,17] The experimental set-up consists of a rotating platform, as in Fig. 10 on which the quasi-conical structure to be measured is installedand a camera fixed on a tripod to take pictures of the sample.…”

Section: Minimum Circumferential Deformationmentioning

confidence: 99%

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Comparison between Finite Elements simulation of residual stress and Computer Vision measurements in a welding TIG process

Petrucci¹,

Bianchi²,

Scappaticci³

et al. 2021

Diagnostyka

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In this work, residual stresses arising after an industrial TIG welding process on an aerospace grade part are investigated. The customer demand for high product resistance and high dimensional accuracy calls for the control of the welding process and the minimisation of the residual stresses. Dimensional check of manufactured parts was traditionally performed in a quality room by means of coordinate measuring machines (CMM). For parts larger than 1 meter, this operation shows several issues, as the handling and the need for large and expensive measuring devices. These needs can be fulfilled by an innovative method that, through continuous dimensional check, allows to optimise the welding process parameters. This method is built on a post-process measurement of part shrinkage based on a Computer Vision technique, the outcome being a 3D reconstruction of the actual part. Moreover, the whole procedure is low-cost and time saving, as it can be performed with a conventional camera mounted on a tripod. A Finite Element Model (FEM) of the TIG process on the selected sample was developed. The result of the numerical model was compared with the Computer Vision-based post-process measurement. The simulation scenario predicted by Finite Element Analysis agrees with measurements.

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Section: Minimum Circumferential Deformationmentioning

confidence: 99%

“…Ali et al [15], attempted to detect defect on small cylindrical pieces by means of a quite sophisticated mirror-based device. Xiao et al [16] monitored the dimensional accuracy of a small conical workpiece on a rotating platform with a fixed camera. In [17] a similar work was carried on, to check roundness of an automotive camshaft.…”

Section: Introductionmentioning

confidence: 99%

Comparison between Finite Elements simulation of residual stress and Computer Vision measurements in a welding TIG process

Petrucci¹,

Bianchi²,

Scappaticci³

et al. 2021

Diagnostyka

View full text Add to dashboard Cite

show abstract

“…To monitor the SLM forming process effectively, machine vision inspection is a safe, reliable, and highly automated non-contact inspection technology that can mimic human eye functions through industrial cameras and extract effective information from various environments [ 13 ]. The application of this technology in the industrial field is relatively large, mainly involving the detection of surface defects in metals, fabrics, glass, electronic devices, etc.…”

Section: Introductionmentioning

confidence: 99%

A New Method for Automatic Detection of Defects in Selective Laser Melting Based on Machine Vision

et al. 2021

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Selective laser melting (SLM) is a forming technology in the field of metal additive manufacturing. In order to improve the quality of formed parts, it is necessary to monitor the selective laser melting forming process. At present, most of the research on the monitoring of the selective laser melting forming process focuses on the monitoring of the melting pool, but the quality of forming parts cannot be controlled in real-time. As an indispensable link in the SLM forming process, the quality of powder spreading directly affects the quality of the formed parts. Therefore, this paper proposes a detection method for SLM powder spreading defects, mainly using industrial cameras to collect SLM powder spreading surfaces, designing corresponding image processing algorithms to extract three common powder spreading defects, and establishing appropriate classifiers to distinguish different types of powder spreading defects. It is determined that the multilayer perceptron (MLP) is the most accurate classifier. This detection method has high recognition rate and fast detection speed, which cannot only meet the SLM forming efficiency, but also improve the quality of the formed parts through feedback control.

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“…Feng [9] has employed a single-mode fiber-coupled laser module for straightness measurement to enlarge the measuring range. Xiao et al [10] realized the real-time measurement of straightness and roundness of spun workpieces during spinning by obtaining real-time images based on machine vision technology. Chu et al [11] proposed a digital image-based method for the overall structural deformation monitoring, utilizing the image perspective transformation and edge detection.…”

Section: Introductionmentioning

confidence: 99%

An Enhanced Detection System of Drill Rod Bending Degree Based on Two-Dimensional Laser

Wen

Wang

et al. 2020

Sensors

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Drill rod straightness has to be strictly controlled and the maximum bending degree detection needs to be used in the straightening process. The mechanical bending degree measurement depends on machinery instruments and workers’ experience, often with low efficiency and precision. While the optical inspection, as a non-contact detection method, with higher precision and lower installation accuracy requirements, is frequently applied in the online detection system. Based on this, an enhanced bending degree detection system for a drill rod is proposed in this paper. Compared to the existing detection system, the main progress is to use a two-dimensional laser to quickly obtain arc profile data and fit with ellipse. Segment inspection idea is also utilized is this system as the camera that could obtain the whole drill rod in one shot needs extremely high resolution and price. A specialized algorithm is designed to fit the cross-section shape and whole centerline displacement based on the least square method. Some laboratory tests are conducted to verify this detection system, findings of which are compared to manual measured results. The maximum bending degree error is 2.14 mm and the maximum position error is 8.21 mm, which are both within the tolerance of error. Those results show the feasibility and precision of this enhanced detection system.

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Research on the on-line dimensional accuracy measurement method of conical spun workpieces based on machine vision technology

Cited by 48 publications

References 14 publications

Comparison between Finite Elements simulation of residual stress and Computer Vision measurements in a welding TIG process

Comparison between Finite Elements simulation of residual stress and Computer Vision measurements in a welding TIG process

A New Method for Automatic Detection of Defects in Selective Laser Melting Based on Machine Vision

An Enhanced Detection System of Drill Rod Bending Degree Based on Two-Dimensional Laser

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