Industrial
Vibration and Acoustic Analysis
Spectral features plus CNN classifiers; Augury, Emerson AMS linked to Mtell.
Named Models
The research names no model for this use case.
Where this comes from
Models the research names for this use case. Research, with sources on each model record.
Who Runs It
No deployment is recorded for this use case.
Where this comes from
Documented uses by named organisations. The evidence column says who made the claim.
Candidate Models
TSB-AD
A general benchmark for this model class, not a test on this use case. Time-series anomaly detection, 1,070 series from 40 datasets (VUS-PR); NeurIPS 2024; open to community submissions from 1 Apr 2026. Higher is better.
PaAnoSungkyunkwan University vendor-reported0.53(Sub)-PCA independent0.42
MOMENT (MOMENT-1-large)Carnegie Mellon University independent0.39DeepAnT independent0.31OmniAnomaly maintainer-run0.31PCA independent0.3100.51
TimesFM 3.0Google, time seriesReleasedAug 2026open weightshas scoreslast 18 months
Toto 2.0 1BDatadog, time seriesReleasedJun 2026open weightshas scoreslast 18 monthsToto 2.0 2.5BDatadog, time seriesReleasedJun 2026open weightshas scoreslast 18 monthsToto 2.0 313MDatadog, time seriesReleasedJun 2026open weightshas scoreslast 18 months
Granite PatchTST-FM r1IBM, Rensselaer Polytechnic Institute, time seriesReleasedMar 2026open weightshas scoreslast 18 months
Moirai 2.0 smallSalesforce, time seriesReleasedNov 2025open weightshas scoreslast 18 months
Chronos-2Amazon, time seriesReleasedOct 2025open weightshas scoreslast 18 monthsFlowState r1.1IBM, time seriesReleasedSep 2025open weightshas scoreslast 18 monthsTimesFM 2.5Google, time seriesReleasedSep 2025open weightshas scoreslast 18 months
TiRexNX-AI, time seriesReleasedMay 2025open weightshas scoreslast 18 monthsShowing 10 of 68. All models of this class
Where this comes from
Derived, not researched: models in the directory whose class matches a class this use case uses, excluding family records and models shut down or deprecated. Ranked by how many fit facts they meet, then by release date. Each fit fact is read from the model record.
Links
Modelsnone recorded
Who Runs Itnone recorded
Sources
- Towards a more realistic evaluation of machine learning models for bearing fault diagnosis arxiv.org https://arxiv.org/abs/2509.22267v1
- Press Archives augury.com https://www.augury.com/media-center/press/
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "Vibration and Acoustic Analysis", https://aurion.semai.id/usecases/ind-vibration-acoustic/, records of October 2026.