NC machining verification algorithm based on the STL model

An algorithm to assess the deviation of a machined workpiece model for a nominal part of the stereolithography (STL) model-based numerically controlled (NC) machining verification is presented, which is inspired by several algorithms used for evaluating the difference between two triangular meshes o...

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Bibliographic Details
Published in:International journal of advanced manufacturing technology Vol. 110; no. 5-6; pp. 1153 - 1161
Main Authors: Miao, Ying, Song, Xiaowen, Wang, Jun, Lu, Zhonghua
Format: Journal Article
Language:English
Published: London Springer London 01.09.2020
Springer Nature B.V
Subjects:
Algorithms
CAE) and Design
Computer-Aided Engineering (CAD
Engineering
Errors
Industrial and Production Engineering
Lithography
Machining
Mechanical Engineering
Media Management
Original Article
Sampling
Verification
Workpieces
Signed distance
Background grid
NC machining verification
Sampling step
STL model
ISSN:0268-3768, 1433-3015
Online Access:Get full text
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Summary:An algorithm to assess the deviation of a machined workpiece model for a nominal part of the stereolithography (STL) model-based numerically controlled (NC) machining verification is presented, which is inspired by several algorithms used for evaluating the difference between two triangular meshes of similar shape, and some improvements are made. First, each triangle of the machined workpiece model is sampled under a user-defined sampling step δ . Then, the signed distance between each sample and the nominal part is computed to obtain the maximal error, minimal error, and mean error between the two STL models. Finally, a background grid is constructed to quickly search for the triangle closest to the sampling point. The experimental results demonstrate that the accuracy can be improved by sampling all the triangles, including those too small to be sampled under the current sampling step δ . The efficiency can be increased by applying a background grid, and the undercut and overcut areas can be easily detected by coloring the machined workpiece model according to the signed distance associated with each sample.
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ISSN:0268-3768
1433-3015
DOI:10.1007/s00170-020-05867-w