Ms. Jingjing Fan Profile

Jingjing Fan

Researcher at Beihang Univ

SPIE Involvement:

Author

Publications (3)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 21 August 2020 Presentation + Paper

A method of registering point cloud with CAD model based on line contour matching

Jingjing Fan, Liqun Ma, Zhi Zou

Proceedings Volume 11509, 1150907 (2020) https://doi.org/10.1117/12.2570494

KEYWORDS: 3D modeling, Reverse modeling, 3D image processing, 3D scanning, Computer vision technology

Read Abstract +

Registration of point cloud with its CAD model can be used to detect products. To register point cloud with its CAD model, feature characters are used. In this article, a registration method based on line contour matching is proposed. The registration process includes two parts. The one is to extract line contour points (LCPs) from point cloud. The other is to match LCPs of point cloud with LCPs of CAD model. To extract LCPs from point cloud, a slice set is constructed to extract section line data (SLD) containing LCPs from point cloud. Then LCPs are identified by judging the feature end of SLD and analyzing normal angle sequence (NAS) of SLD. LCPs of CAD model are non-uniformly distributed. So to make the matching process more efficient and robust, two groups of LCPs are uniformly sampled. Then best fitting method is used to match the two groups of sampled LCPs to obtain transformation parameters. Verification experiments are conducted on three line contours. And the calculated transformation parameters are compared with reference values. The results show that the deviations of rotation angle are within (-0.9°~0.3°). And deviations of translation elements are within ±0.4mm.

Proceedings Article | 17 April 2020 Paper

An approach of calculating minimal distance between assembled engine pipes based on scanned cloud points

Jingjing Fan, Liqun Ma, Zhi Zou

Proceedings Volume 11455, 114551Y (2020) https://doi.org/10.1117/12.2563386

KEYWORDS: Clouds, Lithium, Picosecond phenomena, Fluctuations and noise, Astronomical engineering

Read Abstract +

Minimal distance between engine assembled pipes is an important parameter for evaluating the assembling quality. Feeler gauge is a traditional method, which is time-consuming and low accuracy. In this article, a new approach is proposed which employs an accurate 3D scanner to obtain the surface cloud points of pipes, then extracting the pipe center lines to calculate the minimal distance of two pipes. Firstly, points belonging to the same pipe were picked up. Then equal-interval grids were built along a coordinate direction in which the pipe stretched longest. Point cloud was divided into grid according to its coordinates. Center points of all grids constituted rough tendency points of a pipe. Then, a vertical plane was built on each tendency point passing through it. Then point cloud of the pipe was projected onto the nearest plane. And on each plane, the projected points were fitted into a circle. The center points of all circles constituted center-line points of a pipe. Then traversing method was used to calculate rough minimal-distance (RMD) between two center lines. Then a searching process is conducted around the minimal-point-pair to further calculate minimal distance of two center lines. And minimal-distance of two pipe surfaces was calculated by subtracting radii of two pipes from the minimal-distance of center-line points. Four groups of pipes were examined to verify the proposed strategy. The results showed that the deviations of minimal-distance of two pipe surfaces were within -0.35mm~0.46mm. And the deviations of pipe radius were within-0.1mm~0.29mm.

Proceedings Article | 23 August 2017 Presentation + Paper

Form and position measurement of sheet metal parts by boundary outlines extracting strategy

Liqun Ma, Jingjing Fan, Zili Zhou, Yongqian Li

Proceedings Volume 10373, 1037306 (2017) https://doi.org/10.1117/12.2271590

KEYWORDS: Inspection, Clouds, Manufacturing, Opto mechatronics, Metrology, Laser scanners, Data storage, Calibration

Read Abstract +

This paper proposes a new strategy of extracting boundary points from scanning point cloud (SPC) data of sheet metal parts (SMPs). This strategy is suitable for bending SMPs with slowly changing surfaces. To cope with the problem that the SMP is too thin to have enough points of its lateral surface to be calculated for the boundary outline, the boundary points are obtained by moving ridge points which is the maximum curvature points on the marginal of parts along theoretical position direction. In this article, the strategy is explained firstly and then carried out on two different experimental SMPs. The strategy contains several steps. Firstly, we construct a slice set called multiple direction slices (MDS) along a curve fitted by boundary points of SPC. Then marginal point data (MPD) is obtained completely and accurately by MDS. And then the chamfer arc data is extracted from MPD by setting identification model of chamfer arc’s two endpoints. Then the ridge points which are the maximal curvature points of chamfer arc data are picked out from chamfer arc data. Finally, by moving the ridge points along a certain direction for a fixed distance, the boundary points are calculated out. Two experiments are carried out to identify position error and form error of the extracted boundary points. The measurement results of boundary outlines of a 6mm thick SMP from a three coordinate measuring machine (CMM) is taken as reference in the first experiment. The second experiment regards theoretical boundary outline as reference. Both two experiments demonstrate the effectiveness of the strategy.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years