Papers by Author: Jing Bin Hao

Abstract: To efficiently decompose a large complex STL model, an improved boundary extraction method is proposed based on genetic algorithm. Three curvature parameters (dihedral angle, perimeter ration and convexity) were used to estimate the surface curvature information. Genetic Algorithm (GA) is used to determinate the threshold of feature edge. The discrete feature edges are grouped and filtered using the best-fit plane (BFP), which is calculated by Least Square Method (LSM). Several experimental results demonstrate that the amount of feature edges is about half of the preset threshold method, and useful feature edges were reserved. The extracted feature boundaries can be directly used to decompose large complex models.

Abstract: The asynchronous linear hotwire cutting (ALHC) system of expandable polystyrene (EPS) foam is a new rapid prototyping (RP) technology, which uses the asynchronous linear hotwire cutter and EPS foam to fabricate the part. The efficiency and capacity of ALHC system depends significantly on the pre-process of STL model. This paper presents an original algorithm for adaptively decomposing a STL model into a set of variable slices, which can be efficiently fabricated by ALHC system. A large complex model is first partitioned into several smaller and simpler sub-models by using the curvature-based partitioning. Then, these sub-models are sliced into layers with different thickness based on feature facets. Several experimental results demonstrate the reliability and efficiency of the slicing algorithm.