---
license: mit
configs:
- config_name: source_metadata
  data_files:
  - split: train
    path: source_metadata/*.parquet
- config_name: bearings
  data_files:
  - split: train
    path: bearings/*.parquet
- config_name: gearboxes
  data_files:
  - split: train
    path: gearboxes/*.parquet
- config_name: v2_train
  data_files:
  - split: train
    path: v2_train/*.parquet
---

# Mechanical Components Vibration Dataset

Comprehensive multi-source mechanical vibration dataset for training cross-component fault diagnosis and prognostics models. Designed for the Mechanical-JEPA project.

**Total: ~12,000+ samples | 9.5 GB | 16 sources | 5 component types**

## Quick Start

```python
from datasets import load_dataset

bearings = load_dataset("Forgis/Mechanical-Components", "bearings", split="train")
gearboxes = load_dataset("Forgis/Mechanical-Components", "gearboxes", split="train")
sources = load_dataset("Forgis/Mechanical-Components", "source_metadata", split="train")
```

## Two-Level Schema

**source_metadata** (16 entries): One row per source dataset with constant properties.
**bearings/gearboxes** configs: Per-sample data linked via `source_id` foreign key.

## Dataset Sources

### Bearings (~10,000 samples from 10 sources)

| Source | Samples | Component | Sensors | Unique Value |
|--------|---------|-----------|---------|--------------|
| [CWRU](https://engineering.case.edu/bearingdatacenter) | 40 | Ball bearing | Vibration | Standard benchmark |
| [MFPT](https://www.mfpt.org/fault-data-sets/) | 20 | Ball bearing | Vibration | Variable load |
| [FEMTO](https://www.nasa.gov/content/prognostics-center-of-excellence-data-set-repository) | 3,569 | Ball bearing | Vibration, temperature | Run-to-failure (RUL) |
| [Mendeley](https://data.mendeley.com/datasets/vxkj334rzv/7) | 280 | Ball bearing | Vibration | **Speed transitions** (action-conditioning) |
| [XJTU-SY](https://github.com/WangBiaoXJTU/xjtu-sy-bearing-datasets) | 1,370 | Ball bearing | Vibration | Run-to-failure (RUL) |
| [IMS/NASA](https://data.nasa.gov/dataset/ims-bearings) | 1,256 | Ball bearing | Vibration | Run-to-failure (RUL) |
| [Paderborn](https://mb.uni-paderborn.de/kat/forschung/bearing-datacenter/) | 384 | Ball bearing | Vibration, **current** | Real + artificial faults |
| [MAFAULDA](https://www02.smt.ufrj.br/~offshore/mfs/page_01.html) | 800 | **Shaft+bearing** | Vibration, **acoustic**, tachometer | **Imbalance, misalignment** (shaft faults!) |
| [Ottawa](https://data.mendeley.com/datasets/y2px5tg92h/1) | 180 | Ball bearing | Vibration, **acoustic** | **Cage faults**, 3 health stages |
| [SCA Pulp Mill](https://data.mendeley.com/datasets/tdn96mkkpt/2) | 2,663 | Industrial bearing | Vibration | **Real industrial data** |
| [VBL-VA001](https://zenodo.org/records/7006575) | 800 | Shaft+bearing | Vibration (triaxial) | Misalignment, unbalance |
| [SEU](https://github.com/cathysiyu/Mechanical-datasets) | 140 | Drivetrain bearing | 8-ch (motor+gearbox) | Cross-component rig |

### Gearboxes (~1,225 samples from 4 sources)

| Source | Samples | Component | Sensors | Unique Value |
|--------|---------|-----------|---------|--------------|
| [OEDI](https://data.openei.org/submissions/623) | 20 | Spur gear | Vibration (4-ch) | Healthy vs gear crack |
| [PHM 2009](https://phmsociety.org/public-data-sets/) | 109 | Spur gear | Vibration, tachometer | Challenge data |
| [MCC5-THU](https://github.com/liuzy0708/MCC5-THU-Gearbox-Benchmark-Datasets) | 956 | Spur gear | Vibration | **Speed/load transitions** |
| [SEU](https://github.com/cathysiyu/Mechanical-datasets) | 140 | Planetary+parallel | 8-ch (motor+gearbox) | Cross-component rig |

## Component Types Covered

| Component | Sources | Fault Types |
|-----------|---------|-------------|
| **Bearings** | CWRU, MFPT, FEMTO, Mendeley, XJTU-SY, IMS, Paderborn, Ottawa, SCA | inner_race, outer_race, ball, cage, compound, degrading |
| **Gears** | OEDI, PHM2009, MCC5-THU, SEU | gear_crack, gear_wear, missing_tooth, tooth_break |
| **Shafts** | MAFAULDA, VBL-VA001 | imbalance, misalignment_horizontal, misalignment_vertical |
| **Drivetrains** | SEU | Combined motor+gearbox+bearing from single rig |
| **Industrial** | SCA Pulp Mill | Naturally occurring faults in real machinery |

## Sensor Modalities

| Modality | Sources | Channels |
|----------|---------|----------|
| **Vibration** (accelerometer) | All 16 | 1-8 channels per sample |
| **Motor current** | Paderborn, Mendeley (partial) | 2-3 phase current |
| **Acoustic** (microphone) | MAFAULDA, Ottawa | 1 channel |
| **Tachometer** | MAFAULDA, PHM2009, OEDI | 1 channel |
| **Temperature** | FEMTO | Scalar in slow_signals |
| **Torque** | SEU, MCC5-THU | 1 channel |

## Key Features

- **412 transition samples** for action-conditioning (Mendeley speed ramps + MCC5-THU speed/load transitions)
- **Episode/RUL fields** for prognostics (FEMTO, XJTU-SY, IMS, SCA)
- **Real industrial data** from SCA pulp mill (not lab)
- **Shaft faults** (imbalance, misalignment) from MAFAULDA and VBL-VA001
- **Acoustic data** from MAFAULDA and Ottawa (microphone alongside accelerometer)
- **Cross-component** drivetrain data from SEU (motor+gearbox+bearing on single rig)

## Per-Sample Schema

```python
{
    "source_id": "cwru",            # FK to source_metadata
    "sample_id": "cwru_105",
    "signal": [[0.1, 0.2, ...]],    # (n_channels, signal_length)
    "n_channels": 2,
    "channel_names": ["DE_accel", "FE_accel"],
    "channel_modalities": ["vibration", "vibration"],
    "health_state": "faulty",       # healthy | faulty | degrading
    "fault_type": "inner_race",
    "fault_severity": None,
    "rpm": 1750,
    "load": 2.0,
    "load_unit": "hp",
    "episode_id": None,             # For run-to-failure
    "episode_position": None,       # 0.0 to 1.0
    "rul_percent": None,            # Remaining useful life
    "is_transition": False,         # Speed/load change
    "transition_type": None,        # ramp_speed | ramp_load
}
```

## v2 Training-Ready Config (Planned)

A standardized config for direct model training:
- Fixed sampling rate: 12,800 Hz
- Fixed window: 16,384 samples (1.28 seconds)
- Vibration-only (single modality)
- Per-sample instance normalization
- Source-disjoint train/val/test splits


## v2 Training-Ready Config (LIVE)

Standardized for direct model training. All sources resampled to common format.

```python
# Load training-ready data (all splits in one, filter by 'split' column)
v2 = load_dataset("Forgis/Mechanical-Components", "v2_train", split="train")
v2_train = v2.filter(lambda x: x["split"] == "train")  # 20,143 samples
v2_val = v2.filter(lambda x: x["split"] == "val")      # 1,332 samples
v2_test = v2.filter(lambda x: x["split"] == "test")    # 6,363 samples
```

| Parameter | Value |
|-----------|-------|
| Sampling rate | 12,800 Hz |
| Window length | 16,384 samples (1.28 seconds) |
| Channels | 1 (primary vibration) |
| Normalization | Per-sample instance norm |
| Splits | Source-disjoint (train/val/test) |

**Train** (12 sources): CWRU, MFPT, FEMTO, XJTU-SY, IMS, OEDI, PHM2009, MCC5-THU, SEU, MAFAULDA, VBL, SCA-train
**Val** (2 sources): Paderborn, Ottawa
**Test** (2 sources): Mendeley, SCA-test

## Citations

Please cite the original datasets. See source_metadata config for full citations per source.