README.md

---
dataset_info:
  features:
  - name: query
    dtype: string
  - name: image
    dtype: image
  - name: annot
    dtype: string
  - name: reasoning
    dtype: 'null'
  - name: cate
    dtype: string
  - name: task
    dtype: string
  - name: metadata
    dtype: string
  splits:
  - name: train
    num_bytes: 45112111.0
    num_examples: 690
  - name: test
    num_bytes: 15718805.0
    num_examples: 217
  download_size: 60104829
  dataset_size: 60830916.0
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
tags:
- bearing-fault-diagnosis
- vibration
- signal-to-image
- xjtu-sy
- run-to-failure
- compute-then-check
license: cc-by-4.0
task_categories:
- image-classification
pretty_name: XJTU-SY Bearing Run-to-Failure — Envelope Spectrum (signal→VLM, Category
  C)
---
# XJTU-SY — fault classification from the envelope spectrum (reasoning track)

Third signal dataset in the AI4Manufacturing FORGE corpus (Category **C**, task **T-C1**), from 15 accelerated **run-to-failure** tests. Each record is the **envelope spectrum** of a 1.28 s vibration snapshot with the characteristic fault frequencies marked — the representation for faithful **compute-then-check** CoT. `reasoning` is empty; a planned **`XJTU-annotated`** sibling will fill it (not yet published).

**Records:** 907 (splits {'train': 690, 'test': 217}); labels {'normal': 416, 'outer_race': 352, 'inner_race': 139}; evidence_tier {'confirmed': 907}.

## Schema (7-field unified record)
| field | meaning |
|---|---|
| `query` | the classification instruction (one of 30 deterministic paraphrases per representation) |
| `image` | the rendered signal image (bytes embedded) |
| `annot` | gold fault class: normal / inner_race / outer_race |
| `reasoning` | chain-of-thought (empty here; filled in the `-annotated` sibling) |
| `cate` / `task` | `C` / `T-C1` (signal fault classification) |
| `metadata` | JSON string: representation, condition, bearing_id, file_number, time_frac, life_files, channel, bearing, rpm, fs, fr_nominal, fr_used, fr_source, features, fault_freqs, computed_verdict, computed_snr, evidence_tier, image_sha256, split |

## Provenance & reproducibility
Generated **deterministically** by `forge_agent/examples/xjtu/convert.py` (`250c7e5f89`) → `forge_model/XJTU/convert_xjtu.py` (`229ee98152`); see `provenance.json`.

**Gold = the documented teardown failure element** (Table 3 of the dataset paper): outer_race = bearings 1_1/1_2/1_3/2_2/2_4/2_5/3_1/3_5, inner_race = 2_1/3_3/3_4. `normal` = early files (before min(30% of life, the data-driven degradation onset)); bearings whose onset is floor-bound (degrading from day one) contribute no normals. Each record was scored under both the nominal and a spectrum-refined shaft rate (rigs deviate 0.5–2% from nominal); the better envelope-pattern match won.

## Caveats
- **Evidence-gated, conflict-free release.** The reasoning track keeps only `confirmed` records (the label-independent envelope-spectrum detector independently finds the documented fault). The perception tracks keep `confirmed` + non-conflicting `weak`; records where the detector confidently found a **different** pattern than the gold (e.g. bearing 2_5's healthy shaft harmonic aliasing into BPFI within 1.7%) are dropped — an image should never fight its own label.
- **`cage` is EXCLUDED from this release.** XJTU has two cage-failure bearings, but only 6/142 files confirm a cage (FTF-ladder) signature — and 57 fault files score as outer_race instead (a failing cage hammers the outer raceway; 8×FTF ≡ BPFO for this geometry). Retained in the raw form; the cage bearings' certified-healthy early files still serve as `normal`. Published classes: **normal / inner_race / outer_race**.
- **TRUE bearing-wise split** — the first run-to-failure set with enough bearings for it: test = whole held-out bearings (1_3, 2_5 outer; 3_3 inner; plus cage bearing 2_3, which after the cage exclusion contributes early-life `normal` records only), so evaluation is on unseen bearings; `normal` appears in both splits from disjoint bearings. Compound-failure bearings (1_5, 3_2) appear only as early-life `normal`.
- **End-of-life masking** — in the final ~3% of life, broadband breakdown can mask the discrete fault comb, so late windows are not uniformly `confirmed`. A property of the physics, not the converter.

## Source & license
Source: **XJTU-SY bearing datasets** — Xi'an Jiaotong University & Changxing Sumyoung Technology; 15 LDK UER204 bearings run to failure under 3 conditions (2100/2250/2400 rpm, 12/11/10 kN); horizontal-channel accelerometer snapshots (25.6 kHz, 1.28 s per minute). Cite: B. Wang, Y. Lei, N. Li, N. Li, *IEEE Trans. Reliability* 69(1):401–412, 2020 (DOI 10.1109/TR.2018.2882682). Gold labels: Table 3 of Lei et al., *J. Mech. Eng.* 55(16), 2019 (DOI 10.3901/JME.2019.16.001). Released by the authors for research use (biaowang.tech/xjtu-sy-bearing-datasets).