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pyGCodeDecode

Authors: Knirsch, Jonathan; Frölich, Felix; Hof, Lukas; Wittemann, Florian; Kärger, Luise;
Abstract

This package reads the target trajectory firmware settings changes from a GCode file. Subsequently, it simulates a motion planner with acceleration and jerk or junction control respectively. The more accurate modeling is achieved by replicating grbl's and its derivatives' firmware-specific movement planner solutions, such as "Classic Jerk" and "Junction Deviation", as an interpretation for Jerk. The simulation result is a description of the nozzle and extrusion axis position and velocity over time and is easily accessible for further analysis. For example it can be used to generate time dependent boundary conditions, needed in additive manufacturing simulations for the Fused Filament Fabrication (FFF) process. The package includes 3D plotting functions, so it can be used to visualize local velocities before printing to improve your process understanding.

For the analysis of GCode, slicers or dedicated analyzer tools, such as Prusa Slicer or gCodeViewer, merely display target process parameters. The actual process velocity however is determined by the firmware of the printer. Velocities are expected to deviate significantly from the target velocity at times of acceleration and deceleration. pyGCodeDecode aims to model the machine's actual behavior and visualize its influence.

Related Organizations
Keywords

FDM, Process Simulation, Additive Manufacturing, Machine Code, 3D Printing, Engineering, MEX, Material Extrusion, Firmware, Fused Filament Fabrication, FFF, Fused Deposition Modeling, GCode, Simulation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average