Data set for "Generalisable 3D printing error detection and correction via multi-head neural networks"

The dataset contains 1,272,273 labelled images of the the extrusion 3D printing process. A camera mounted next to the nozzle of the printer was used to capture images of material deposition for 192 different printed parts covering a range of geometries, material colours, and lighting conditions. Each image is labelled with: flow rate, lateral speed, Z offset, hotend temperature, hotend target temperature, bed temperature, timestamp, and nozzle tip x and y coordinates. To collect the data an automated pipeline was created to acquire and automatically label images from a fleet of 8 extrusion printers and to sample different combinations of printing parameters.

The dataset provides a CSV of 948,396 pre-filtered images where complete failures, parameter outliers, dark images, and images just after parameter changes are removed. A raw CSV is also included labelling all images in the dataset. This dataset can be used for numerous applications such as real-time error detection, closed-loop control, and parameter prediction.

本数据集包含1,272,273张带标注的挤出式3D打印（extrusion 3D printing）过程图像。研究人员在打印机喷头旁安装摄像头，针对192种具备不同几何结构、耗材颜色与光照条件的打印件，采集其耗材沉积过程的图像。每张图像均附带以下标注参数：耗材流量、横向移动速度、Z轴偏移量、热端温度、热端目标温度、热床温度、时间戳，以及喷头尖端的X、Y坐标。为采集该数据集，研发团队搭建了自动化采集流水线，可对由8台挤出式3D打印机组成的集群完成图像采集与自动标注，并可采样不同打印参数的组合。
本数据集附带一份包含948,396张经过预筛选图像的逗号分隔值（CSV）文件，该文件已剔除打印完全失效、参数异常、画面过暗以及参数调整后即刻拍摄的图像。此外还提供一份原始CSV文件，用于标注数据集中的全部图像。该数据集可应用于诸多场景，例如实时故障检测、闭环控制以及打印参数预测等。