Automatic evaluation of machining allowance of precision castings based on plane features from 3D point cloud

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Date: Dec. 2013
From: Computers in Industry(Vol. 64, Issue 9)
Publisher: Elsevier B.V.
Document Type: Article
Length: 206 words

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Abstract :

To link to full-text access for this article, visit this link: Byline: Xudong Li, Wei Li, Hongzhi Jiang, Huijie Zhao Abstract: A novel automatic precision casting machining allowance evaluation approach, which is accomplished by a two-step rough-precise point cloud registration based on plane features extracted from the two point clouds (i.e. the measured precision casting point cloud and the point cloud discretized from the CAD model), is proposed in this paper. Firstly, the two point clouds are registered roughly by PCA algorithm. Secondly, an improved plane fitting and merging algorithm is proposed to extract the plane features from both the two point clouds. The extracted plane features are matched by searching the nearest plane feature description vector. The rotation matrix for the precise registration can then be derived by registering the normal vectors of the matched plane features. Finally, the machining allowance at each point is obtained by calculating the distance between the corresponding points along the normal direction. The experiment on precision casting machining allowance evaluation is given to show the performance of the proposed approach. Author Affiliation: School of Instrumentation Science and Opto-electronics Engineering, Beihang University, Beijing 100191, China Article History: Received 3 September 2012; Revised 13 March 2013; Accepted 5 June 2013

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Gale Document Number: GALE|A349010196