New method to improve range and precision on 3D surface measurement

2003 ◽  
Author(s):  
Wenjing Chen ◽  
Xianyu Su ◽  
Yiping Cao ◽  
Liqun Xiang ◽  
Qican Zhang
Machines ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 13
Author(s):  
Yuhang Yang ◽  
Zhiqiao Dong ◽  
Yuquan Meng ◽  
Chenhui Shao

High-fidelity characterization and effective monitoring of spatial and spatiotemporal processes are crucial for high-performance quality control of many manufacturing processes and systems in the era of smart manufacturing. Although the recent development in measurement technologies has made it possible to acquire high-resolution three-dimensional (3D) surface measurement data, it is generally expensive and time-consuming to use such technologies in real-world production settings. Data-driven approaches that stem from statistics and machine learning can potentially enable intelligent, cost-effective surface measurement and thus allow manufacturers to use high-resolution surface data for better decision-making without introducing substantial production cost induced by data acquisition. Among these methods, spatial and spatiotemporal interpolation techniques can draw inferences about unmeasured locations on a surface using the measurement of other locations, thus decreasing the measurement cost and time. However, interpolation methods are very sensitive to the availability of measurement data, and their performances largely depend on the measurement scheme or the sampling design, i.e., how to allocate measurement efforts. As such, sampling design is considered to be another important field that enables intelligent surface measurement. This paper reviews and summarizes the state-of-the-art research in interpolation and sampling design for surface measurement in varied manufacturing applications. Research gaps and future research directions are also identified and can serve as a fundamental guideline to industrial practitioners and researchers for future studies in these areas.


2012 ◽  
Vol 482-484 ◽  
pp. 2192-2196
Author(s):  
Yuan Tian ◽  
Zi Ma ◽  
Peng Li

For improving precision of 3D surface measurement equipments, which are playing important role in reverse engineering, the Adaptive Network based Fuzzy Inference System (ANFIS) is developed to reconstruct 3D surface error, and the measurement error of point cloud is compensated by the presented 3D error ANFIS model. The precision of 3D surface measurement equipments has been improved noticeably


Author(s):  
Bingjie Xu ◽  
Florian Willomitzer ◽  
Chia-Kai Yeh ◽  
Fengqiang Li ◽  
Vikas Gupta ◽  
...  

2014 ◽  
Vol 7 (2) ◽  
pp. 109-122 ◽  
Author(s):  
Mattia Previtali ◽  
Luigi Barazzetti ◽  
Marco Scaioni

2002 ◽  
Vol 127 (2) ◽  
pp. 234-237 ◽  
Author(s):  
D.L Butler ◽  
L.A Blunt ◽  
B.K See ◽  
J.A Webster ◽  
K.J Stout

2005 ◽  
Vol 295-296 ◽  
pp. 145-150 ◽  
Author(s):  
Liang Chia Chen ◽  
Z.Q. Xu

This research develops an innovative free-form surface scanning system using laser triangulation for 3D dental data required for crown reconstruction. This novel design employs double laser diodes to produce two 45° structured-light lines projecting onto the plaster tooth models and three CCD cameras to capture deformed fringes to achieve fast and accurate 3D surface measurement of plaster tooth models. Effective strategies were implemented to overcome problems such as potential measurement occlusion and data registration inaccuracy, commonly encountered by other data scanning methods. The developed system has distinctive features such as laser projecting angles for complete surface measurement coverage, digitizing accuracy, and compact scanner volume for potential applications on 3D surface digitization of tiny industrial components. Experimental results verified that the proposed system achieves a 20µm digitizing accuracy and possesses fast scanning capability. Maximum one minute is used for a single-tooth model and 30 minutes are used for scanning the whole jaw.


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