- hi, think you'd find this interesting:
https://www.researchgate.net/publication/376877267_Applicati...
uses fault tree analysis to derive likely sources of failure based on subsystems and their relationships. think these methods are empirically useful when straight out of the factory line, but i think tacking on a sort of joint discovery process (grounded q&a session?) along with classification could probs be a good tool to help folks land in a ballpark
was working on something similar with audio classification + ecu logs and research agents checking against manuals for my project truck
- This exploration started wanting to train Gradient Boosted Decision Trees (GBDT) with repair data which I would assume captures sub-system relationships. Unfortunately, it is the most guarded data with only extremely privileged access. For example, dealerships and insurance companies compile all the data and they do not share it with anyone else, nothing has been leaked or leaked and survived.
As much as I wish this was useful for diagnosing mechanical problems, the big take away is being able to scrape audio of thousands videos, cleaning the data isolating music, speech, and engine sounds, and capturing all the related text from title, comments, ocr, and transcription for labelling the training data. Granted all this data is copyright, I wouldn't use it outside of a toy for a commercial project. Moreover, when a mechanic diagnosis with sound, they will use a stethoscope.
- Backyard (fault) tree mechanic FTW!
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32 points by dataviz1000 3 days ago | 3 comments