论文标题
3D打印中的异常检测数据集
Dataset for anomalies detection in 3D printing
论文作者
论文摘要
如今，物联网在许多领域都起着重要作用。尤其是，工业4.0正在大量使用智能传感器和大数据分析等概念。物联网设备通常用于监视行业机器并检测其工作中的异常情况。在本文中，我们介绍并描述了来自工作3D打印机的一组数据流。除其他外，它包含打印机头的加速度计数据，入侵能力和打印机元件的温度。为了获得数据，我们导致将几种应用于3D模型应用。因此，结果数据集可用于异常检测研究。
Nowadays, Internet of Things plays a significant role in many domains. Especially, Industry 4.0 is making a great usage of concepts like smart sensors and big data analysis. IoT devices are commonly used to monitor industry machines and detect anomalies in their work. In this paper we present and describe a set of data streams coming from working 3D printer. Among others, it contains accelerometer data of printer head, intrusion power and temperatures of the printer elements. In order to gain data we lead to several printing malfunctions applied to the 3D model. Resulting dataset can therefore be used for anomalies detection research.
