A profile measurement method of large aspheric optical surface based on optimal stitching planning

Ye, Shi-wei; Yang, Ping; Peng, Yunfeng

doi:10.1016/j.precisioneng.2016.01.013

Cited by 8 publications

(2 citation statements)

References 17 publications

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“…The magnification of the objective lens is selected according to the required lateral resolution. The minimum number of required sub-surfaces can then be determined and the incremental angle of object rotation for each measurement is calculated, which aims to ensure an optimum 20% overlapped region between sub-surfaces [20]. Hence, the number of sub-surfaces S N and the rotation angle R A can be determined by (1 )…”

Section: Hardware and Software Setup For Data Acquisitionmentioning

confidence: 99%

A self-calibration rotational stitching method for precision measurement of revolving surfaces

Liu

Cheung

Feng

et al. 2018

Precision Engineering

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When measuring revolving objects, it is often desired to obtain not only the geometrical form of the workpiece, but also the topography of the surface, as they both affect the performance of the part. However, holistic measurement of the entire three-dimensional surface of a revolving part is challenging since most surface measurement instruments only have limited measurement ability, where the bottom and the side surfaces cannot be measured. One solution to obtain geometrical form and surface topography information simultaneously is to add a precision axis to rotate the object while performing surface topography measurement. However, this solution requires a high-cost precision rotation stage and adjustable mounting and alignment aids. Moreover, errors in the rotation will be added to the measurement result, which can be difficult to compensate. Stitching is a method often used for measuring revolving surfaces without the need for precision motion axes, as the method is applied at the software level, and errors in the rotation can be compensated by the stitching algorithm. Nevertheless, the overall accuracy of stitching is limited when the number of sub-surfaces is large, since the measurement and stitching error accumulate along the stitching chain. In this paper, a self-calibration rotational stitching method is presented which can compensate for the accumulated error. The self-calibration method utilises the inherent nature of a revolving surface and compensates for the registration error by aligning the last dataset with the first dataset. The proposed method is demonstrated by measuring grinding wheels with a coherence scanning interferometer and simultaneously rotating the grinding wheels with a lowcost stepper-motor. It is demonstrated that the proposed stitching measurement method is effective in compensating for accumulated registration error. The proposed self-calibration rotational stitching method can be easily extended to a wide range of applications for measuring revolving surfaces using various measuring instruments.

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Section: Hardware and Software Setup For Data Acquisitionmentioning

confidence: 99%

A self-calibration rotational stitching method for precision measurement of revolving surfaces

Liu

Cheung

Feng

et al. 2018

Precision Engineering

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“…Zhang et al [9] developed a simultaneous reverse optimizing reconstruction method which is based on system modelling technique for aspheric sub-aperture stitching interferometer. Ye et al [10] used an optimal stitching planning method to measure large aspheric optical surface with ±4 mm range of probe and 20% of overlapped region. Wiegmann et al [11] evaluated the accuracy of the sub-aperture stitching method using virtual experiments and found that the overall accuracy of stitching result outperformed the direct measurement method by a factor of about 3.…”

Section: Introductionmentioning

confidence: 99%

A Gaussian process and image registration based stitching method for high dynamic range measurement of precision surfaces

Liu

Cheung

Cheng

et al. 2017

Precision Engineering

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Please cite this article as: Liu MY, Cheung CF, Cheng CH, Su R, Leach R.K.A Gaussian process and image registration based stitching method for high dynamic range measurement of precision surfaces.Precision Engineering http://dx.doi.org/10. 1016/j.precisioneng.2017.04.017 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. A Gaussian Highlights： It makes use of Gaussian process to model the sub-aperture measurement datasets to obtain the mean surface for registration, which is a novel method as comparing to traditional filtering methods, and provides better registration accuracy. Image registration and z shift method are used to simplify the 6 degrees of freedom 3D point cloud registration to a 3 degrees of freedom registration. Edge intensity data fusion method is used to fuse the overlapped region to provide a better transition between two datasets. It provides a novel stitching solution for a wide range of optical measurement instruments for achieving high dynamic range optical measurement of precision surfaces Abstract: Optical instruments are widely used for precision surface measurement. However, the dynamic range of optical instruments, in terms of measurement area and resolution, is limited by the characteristics of the imaging and the detection systems. If a large area with a high resolution is required, multiple measurements need to be conducted and the resulting datasets needs to be stitched together. Traditional stitching methods use six degrees of freedom for the registration of the overlapped regions, which can result in high computational complexity. Moreover, measurement error increases with increasing measurement data. In this paper, a stitching method, based on a Gaussian process, image registration and edge intensity data fusion, is presented. Firstly, the stitched datasets are modelled by using a Gaussian process so as to determine the mean of each stitched tile. Secondly, the datasets are projected to a base plane. In this way, the three-dimensional datasets are transformed to two-dimensional (2D) images. The images are registered by using an (x, y) translation to simplify the complexity. By using a high precision linear stage that is integral to the measurement instrument, the rotational error becomes insignificant and the cumulative rotational error can be eliminated. The translational error can be compensated by the image registration process. The z direction registration is performed by a least-squares error algorithm and the (x, y, z) translational information is determined. Finally, the overlapped regions of the measurement datasets are fused together by the edge intensity ...

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A fast self-calibration method of line laser sensors for on-machine measurement of honeycomb cores

Qin

Kang

Sun

et al. 2022

Optics and Lasers in Engineering

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A profile measurement method of large aspheric optical surface based on optimal stitching planning

Cited by 8 publications

References 17 publications

A self-calibration rotational stitching method for precision measurement of revolving surfaces

A self-calibration rotational stitching method for precision measurement of revolving surfaces

A Gaussian process and image registration based stitching method for high dynamic range measurement of precision surfaces

A fast self-calibration method of line laser sensors for on-machine measurement of honeycomb cores

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