# Audio Recording Form2 + Machine Learning = Issue Detection? **URL:** \ **Category:** Experimental\ **Created:** [August 31, 2020, 1:20pm UTC](https://forum.formlabs.com/t/audio-recording-form2-machine-learning-issue-detection/28657 "2020-08-31T13:20:57Z")\ **Posts on this page:** 4\ **Page:** 1
**Author:** ![JLYL33](https://sea1.discourse-cdn.com/flex025/user_avatar/forum.formlabs.com/jlyl33/32/10798_2.png) [@JLYL33](https://forum.formlabs.com/u/JLYL33)\ **Post date:** [August 31, 2020, 1:20pm UTC](https://forum.formlabs.com/t/audio-recording-form2-machine-learning-issue-detection/28657/1 "2020-08-31T13:20:57Z")
Hi everyone, Two days ago I heard a loud banging noise just after starting a new print on my Form2. Luckily I immediately found out that I stupidly forgot to attach the wiper after changing the resin tray. I could abort and start over rapidly without any damage to the printer and its accessories. I think I was quite lucky as I did not leave the place right after starting the print. What saved me here is the noise from the machine that gave me quite a hint that something was wrong. I think some sort of sound monitoring could be useful either as a warning or diagnosis tool. I’m not a coder but as a proof of concept I used [Teachable Machine](https://teachablemachine.withgoogle.com/), a machine learning tool from Google and trained it using a microphone near my Form2. I made several classes (Background Noise, Wiper, Build Platform going UP, Build Platform going Down) and the preview seems to be working okay with little samples [you can try it online if you have a microphone to put next to the printer](https://teachablemachine.withgoogle.com/models/3HDwEux7g/). ![teachableMachineForm2](https://us1.discourse-cdn.com/flex025/uploads/formlabs/original/3X/6/c/6cc3b7ce05080d1c516e74c272473d988523f5fd.jpg) I think with more training on specific problematic sounds, and a better method for recording sounds it could make a great inexpensive feature. I am thinking about some noise-related posts in the forum that were related to: - z-axis stepper motor - suction issue - resin tray not mounted well - collision wiper/failing parts I am not keen on reproducing these issues on my printer to train the model but I would totally have a Raspberry Pi with a microphone recording during the print and send me notifications if something weird is recorded. PS: Happy to share TM file with samples (30Mo) PPS: I also tricked TM by sending sliced mp3 recording of the print via a virtual microphone ---
**Author:** ![hoolito](https://sea1.discourse-cdn.com/flex025/user_avatar/forum.formlabs.com/hoolito/32/16517_2.png) [@hoolito](https://forum.formlabs.com/u/hoolito)\ **Post date:** [August 31, 2020, 3:16pm UTC](https://forum.formlabs.com/t/audio-recording-form2-machine-learning-issue-detection/28657/2 "2020-08-31T15:16:02Z")
how would you record ONLY the sounds from the printer and not those of the surroundings? (Privacy issues) Great idea though! I’d very much like to have a self-monitoring printer ---
**Author:** ![JLYL33](https://sea1.discourse-cdn.com/flex025/user_avatar/forum.formlabs.com/jlyl33/32/10798_2.png) [@JLYL33](https://forum.formlabs.com/u/JLYL33)\ **Post date:** [August 31, 2020, 3:46pm UTC](https://forum.formlabs.com/t/audio-recording-form2-machine-learning-issue-detection/28657/3 "2020-08-31T15:46:05Z")
Hey hoollto, If I understand well, once the algo is trained with this tool, it is possible to convert to TensorFlow for local use ([FAQ](https://teachablemachine.withgoogle.com/faq#Saving-&-Exporting)/Can I use my model outside TM?) without worrying having a microphone connected to Google. ---
**Author:** ![rkagerer](https://avatars.discourse-cdn.com/v4/letter/r/439d5e/32.png) [@rkagerer](https://forum.formlabs.com/u/rkagerer)\ **Post date:** [August 31, 2020, 5:35pm UTC](https://forum.formlabs.com/t/audio-recording-form2-machine-learning-issue-detection/28657/4 "2020-08-31T17:35:15Z")
I love this idea. I wish the use of secondary signals like this were explored more widely across products. Another one I wish got more uptake is the use of a feedback loop during printing to tighten tolerances. e.g. There’s a MarkForged printer that measures your model with a laser ranger as it prints, and one could use that kind of input to continuously calibrate and correct for many types of aberration.