3D printing fault detection based on process data

3D printing technology is a kind of rapid prototyping technology. In the 3D printing process, several common faults often happen, resulting in interruption of the printing process or poor-quality of the printed product. In order to maintain normal function of the 3D printer, users need to manually check the scene all the time. In order to perform real-time detection of faults in the printing process of the 3D printer, multiple sets of experiments were conducted. We use sensors to obtain multiple parameters of the 3D printer. The machine learning method is used to classify and detect whether the printing process is in a fault state. This method can effectively detect the fault condition that occurs during real-time 3D printing process and can be promoted in more 3D printers.