scholarly journals Discussion on Reverse Design of Components with Complex Curved Surface and Computer Numerical Control Machining

2018 ◽  
Vol 2 (4) ◽  
Author(s):  
Dapeng Fu ◽  
Xinyu Lv ◽  
Shuangyang Jiang
Keyword(s):  
Data Processing ◽  
Point Cloud ◽  
Tool Path ◽  
Computer Numerical Control ◽  
Numerical Control ◽  
Curved Surface ◽  
Surface Generation ◽  
Point Cloud Data ◽  
Numerical Control Machining ◽  
Cloud Data

Abstract: With the continuous development and advancement of science and technology, the work of tool path planning has received extensive attention. Among them, curved surface generation and data processing are the focus of management and design, which necessitate the full application of reverse design of complex curved surface components to complete numerical control processing, effective optimization and upgrading, integration the tasks of point cloud data collection and point cloud data processing to ensure that the corresponding computer numerical control machining model can exert its actual value. This paper briefly analyzes the basic principles of curved surface reconstruction as well as discusses the reverse design of complex curved components and the experimental processes and results that involved computer numerical control machining, which serves the purpose as reference only.

The Research of Point Cloud Data Processing Technology

2014 ◽  
Vol 628 ◽  
pp. 426-431
Author(s):  
Li Bo Zhou ◽  
Fu Lin Xu ◽  
Su Hua Liu
Keyword(s):  
Data Processing ◽  
Point Cloud ◽  
Quality Data ◽  
Surface Generation ◽  
Point Cloud Data ◽  
Data Smoothing ◽  
Cloud Data ◽  
Data Point ◽  
Cloud Data Processing

Data processing is a key to reverse engineering, the results of which will directly affect the quality of the model reconstruction. Eliminate noise points are the first step in data processing, The method of using Coons surface to determine the noise in the data point is proposed. To reduce the amount of calculation and improve the surface generation efficiency, data point is reduced. According to the surrounding point coordinate information, the defect coordinates are interpolated. Data smoothing can improve the surface generation quality, data block can simplify the creation of the surface. Auto parts point cloud data is processed, and achieve the desired effect.

Reverse Modeling of Vehicle Suspension Control Arm

2013 ◽  
Vol 427-429 ◽  
pp. 1183-1186
Author(s):  
Hai Bo Zhang ◽  
Ying Chang ◽  
Rui Jun Zhang ◽  
Hong Yuan Fan
Keyword(s):  
Point Cloud ◽  
Production Cost ◽  
3D Model ◽  
Modeling Method ◽  
Curved Surface ◽  
Vehicle Suspension ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Suspension Control ◽  
Curved Surface Parts

Reverse modeling of vehicle suspension control arm is studied. Firstly, the data of vehicle suspension control arm is acquired. Secondly, the scanning point cloud data is processed. Then 3D model of vehicle suspension control arm is reconstructed. Finally, models deviation is analyzed to find out the deficiencies and to improve the accuracy of the model. Reverse modeling based on CATIA can make up the shortage of traditional modeling method and solve the problem of gaining the data of complex curved surface parts. It also can shorten the innovation and improvement cycle of the vehicle suspension control arm and reduce the production cost and enhance enterprise competitiveness.

Point Cloud Data Processing Method of Cavity 3D Laser Scanner

2013 ◽  
Vol 33 (8) ◽  
pp. 0812003 ◽  
Author(s):  
陈凯 Chen Kai ◽  
张达 Zhang Da ◽  
张元生 Zhang Yuansheng
Keyword(s):  
Data Processing ◽  
Point Cloud ◽  
Laser Scanner ◽  
Processing Method ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Data Processing Method ◽  
Cloud Data Processing

Triangulation-Based Point Cloud Data Processing Technology Research and Application

2014 ◽  
Vol 610 ◽  
pp. 729-733
Author(s):  
Ke He Wu ◽  
Wen Chao Cui ◽  
Bo Hao Cheng ◽  
Qian Yuan Zhang
Keyword(s):  
Data Processing ◽  
Data Storage ◽  
Point Cloud ◽  
Extraction Process ◽  
Programming Algorithm ◽  
Point Cloud Data ◽  
Boundary Extraction ◽  
Processing Technologies ◽  
Cloud Data ◽  
Cloud Data Processing

With the "Digital Earth" concept being put forward, people are starting to focus on geospatial information technology. Traditional manual building modeling process is gradually eliminated by history due to cumbersome and inefficient work. With massive data storage and processing technologies emerging and improving, people begin to explore building point cloud data measured by laser radar technology and to use point cloud data processing software for further building boundary extraction. In the model boundary extraction process, the use of prototype with the model fit is a good, clear and easy programming algorithm and triangulation algorithm.

scholarly journals Efficient point cloud data processing in shipbuilding: Reformative component extraction method and registration method

2014 ◽  
Vol 1 (3) ◽  
pp. 202-212 ◽  
Author(s):  
Jingyu Sun ◽  
Kazuo Hiekata ◽  
Hiroyuki Yamato ◽  
Norito Nakagaki ◽  
Akiyoshi Sugawara
Keyword(s):  
Data Processing ◽  
Point Cloud ◽  
Accuracy Evaluation ◽  
Point Cloud Data ◽  
Continuous Part ◽  
Registration Method ◽  
Shipbuilding Industry ◽  
Seed Point ◽  
Cloud Data ◽  
Cloud Data Processing

Abstract To survive in the current shipbuilding industry, it is of vital importance for shipyards to have the ship components' accuracy evaluated efficiently during most of the manufacturing steps. Evaluating components' accuracy by comparing each component's point cloud data scanned by laser scanners and the ship's design data formatted in CAD cannot be processed efficiently when (1) extract components from point cloud data include irregular obstacles endogenously, or when (2) registration of the two data sets have no clear direction setting. This paper presents reformative point cloud data processing methods to solve these problems. K-d tree construction of the point cloud data fastens a neighbor searching of each point. Region growing method performed on the neighbor points of the seed point extracts the continuous part of the component, while curved surface fitting and B-spline curved line fitting at the edge of the continuous part recognize the neighbor domains of the same component divided by obstacles' shadows. The ICP (Iterative Closest Point) algorithm conducts a registration of the two sets of data after the proper registration's direction is decided by principal component analysis. By experiments conducted at the shipyard, 200 curved shell plates are extracted from the scanned point cloud data, and registrations are conducted between them and the designed CAD data using the proposed methods for an accuracy evaluation. Results show that the methods proposed in this paper support the accuracy evaluation targeted point cloud data processing efficiently in practice.

LiDAR Point Cloud Data Processing in Autonomous Vehicles

2021 ◽  
Author(s):  
Vani Suthamathi Saravanarajan ◽  
Rung-Ching Chen ◽  
Long-Sheng Chen
Keyword(s):  
Data Processing ◽  
Autonomous Vehicles ◽  
Point Cloud ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Cloud Data Processing

Point Cloud Data Preprocessing Based on the Geomagic

2013 ◽  
Vol 690-693 ◽  
pp. 2817-2820 ◽  
Author(s):  
Feng Chang Xue
Keyword(s):  
Data Processing ◽  
Noise Reduction ◽  
Point Cloud ◽  
Point Cloud Data ◽  
Processing Efficiency ◽  
Cloud Data ◽  
Noise Point ◽  
Isolated Point ◽  
Cloud Process

In the acquisition process of point cloud data, there exist speckles and noise point. This essay, based on geomagic, presents specific technical steps to remove isolated point in vitro, avoid point cloud resampling and remove point cloud noise. Applications showed that geomagic can, from the original point cloud process, find out useful point cloud, delete speckles, and through the methods of resampling and noise reduction processing, improve cloud quality and reduce data deviation thus improving the data processing efficiency.

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