AI4Manufacturing/XJTU-perception

Roles

Roles: perception view of XJTU — annot is the source label (inner_race / normal / outer_race), kept machine-parseable as the gold for verification and reward parsing; the model reads query + image, where the repo ships a bearing's vibration in four image encodings as four equal-sized configs — reshaped (consecutive samples arranged as the rows of a grayscale square), scalogram (a continuous-wavelet time-scale view), spectrogram (a short-time Fourier transform) and waveform (the time-domain trace) — 951 records each, and the query states which encoding the record shows. The reasoning column is empty on all 3,804 records, so this repo is not itself a training view for chain-of-thought and trains annot directly. metadata is provenance (split keys, source identities) and must never be fed to a model.

XJTU-SY — perception representations (visual grounding)

The same XJTU-SY run-to-failure snapshots rendered as perception images — one HF config per representation, for the foundation model's visual grounding. Unlike the XJTU (spectrum) repo, these are not for compute-then-check CoT (reasoning stays empty).

Configs

load_dataset("AI4Manufacturing/XJTU-perception", "spectrogram")

config	records	splits
spectrogram	951	{'train': 709, 'test': 242}
scalogram	951	{'train': 709, 'test': 242}
waveform	951	{'train': 709, 'test': 242}
reshaped	951	{'train': 709, 'test': 242}

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; a planned -annotated sibling will fill it — not yet published)
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 (0574e0e25d) → forge_model/XJTU/convert_xjtu.py (9448e33334); 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).

Overlap / de-duplication (§8)

Cross-family evaluation lock — metadata.eval_lock (stamped 2026-09-20; manifest revision fe6e286912b0, generated 2026-09-08). Every record of this repository, locked or not, carries metadata.eval_lock, computed by forge_model/common/overlap.py::Overlap.stamp_for against common/overlap_manifest.json at that revision — so within this repository the absence of the key cannot occur. Shape: {"locked": bool, "against": [{"repo": …, "split": …}, …], "own_split": …, "manifest_revision": …, "manifest_generated": …}. locked is true when the image is evaluation material anywhere in the corpus; against names every repository and split in which it is (sorted; [] when not locked; it includes the record's own family where that is so); own_split marks a record locked by its own split. The per-record field is the authority — the count here is quoted once, at this revision, and a later manifest may change it: 968 of 3,804 records (968 distinct images) are locked — by column: 0 by the cross-family manifest, 968 by their own split, 0 both ways and counted once; counterparts (records per counterpart; a record can appear under several): none — every lock here is by the record's own split; 968 locked by their own split: test. In words: 968 of the 3,804 records in this repository are evaluation material by their own metadata.split (test: 968) and sit inside the HF split named test / train — under the uniform-split convention the HF split name is a container name, and metadata.split together with metadata.eval_lock carries the truth; a train pool must exclude them. A stamp whose manifest_revision differs from the current manifest is stale, not wrong — recompute it (Overlap.stamp_is_current); a record with no stamp has not been checked against the corpus as it now is. Overlap.partition / assert_train_pool_clean read the field: a train pool built from this repository must exclude every locked record.