In X1 seris, we have a USB camera installed in the corner of the printer chamber. With this camera, we can do a lot of wonderful things, e.g. live video stream, timelapse, and most importantly, realtime monotoring of the printing process. Spaghetti detection, among all the others, is the most important function of printing monitoring.
By the word spaghetti, we mean a board range of printing failures, most of which are just like the famous Italian food spaghetti. However, there are also cases where the filament fragments are not so typically spaghetti-ish, but scattered in small pieces. In our spaghetti detection, all these failures are considered the same kind.
Thanks to the powerful on-chip NPU, we can achive onboard spaghetti detection just inside the printer. Here is the brief procedure:
To have the detector work properly, there are a few requirements.
Same as all the deep learning functions, we highly rely on data. If you have been using this function from the very beginning, you'll notice that we have gained a hugh jump in detection accuracy, but still not high enough. There are always false alarms reported from time to time. We really need your help to improve this function, and it's really simple: join the experience improvement program. The image data will be automatically uploaded to cloud if you join the program.