Reparameterization of ruled surfaces: toward generating smooth jerk-minimized toolpaths for multi-axis flank CNC milling
This paper presents a novel jerk minimization algorithm in the context of multi-axis flank CNC machining. The toolpath of the milling axis in a flank milling process, a ruled surface, is reparameterized by a B-spline function, whose control points and knot vector are unknowns in an optimization-base...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2020 |
| País: | España |
| Institución: | Basque Center for Applied Mathematics (BCAM) |
| Repositorio: | BIRD. BCAM's Institutional Repository Data |
| OAI Identifier: | oai:bird.bcamath.org:20.500.11824/1104 |
| Acceso en línea: | http://hdl.handle.net/20.500.11824/1104 |
| Access Level: | acceso abierto |
| Palabra clave: | Jerk-minimized toolpath B-spline reparameterization ruled surface ruling distance metric multi-axis flank CNC milling |
| Sumario: | This paper presents a novel jerk minimization algorithm in the context of multi-axis flank CNC machining. The toolpath of the milling axis in a flank milling process, a ruled surface, is reparameterized by a B-spline function, whose control points and knot vector are unknowns in an optimization-based framework. The total jerk of the tool's motion is minimized, implying the tool is moving as smooth as possible, without changing the geometry of the given toolpath. Our initialization stage stems from measuring the ruling distance metric (RDM) of the ruled surface. We show on several examples that this initialization reliably finds close initial guesses of jerk-minimizers and is also computationally efficient. The applicability of the presented approach is illustrated by some practical case studies. |
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