Electric Motor Vibrations Dataset — Labeled Motor States [35.1 MB]
Catalog Summary
"Electric-motor vibration sensor dataset from the CHIST-ERA SOON project. ZIP format, 35.1 MB, with labeled functioning states for ML predictive-maintenance experiments."
Catalog Notes
Overview
The Electric Motor Vibrations Dataset contains vibration-sensor data for machine-learning classification and predictive-maintenance experiments.
The experiment used two electrical motors: one tested motor and a second motor used to create a more complex environment and additional noise.
File names encode how the data were obtained and implicitly provide the data labels.
Column Schema
| Column | Description |
|---|---|
| file_name | Encoded file name carrying acquisition context and implicit label information. |
| motor_id | Motor identifier, including tested and auxiliary motors. |
| vibration_signal | Vibration sensor measurement used for motor state classification. |
| operating_context | Acquisition context inferred from file structure and naming. |
| functioning_state_label | Labeled functioning state encoded by file naming and experiment design. |
Key Statistics
- Total Records: Multiple vibration files; exact sample count not stated in metadata
- Features: Vibration sensor data and labels encoded by filenames
- File Format: ZIP archive with vibration data and description PDF
- File Size: 35.1 MB total files
- Time Period: Published 2022
Use Cases
- Electric-motor predictive maintenance
- Vibration-based fault classification
- Condition-monitoring algorithm testing
- Machine-state recognition under noisy environments
Source & Attribution
Created by Adrian Gligor, Laszlo Barna Iantovics, and Alexandru Turc. Published on Zenodo with DOI 10.5281/zenodo.6473455.
View Data Structure
To explore column names, data types, and sample rows, visit the official dataset page on Zenodo.
Preview on ZenodoCite This Dataset
Gligor, A., Iantovics, L. B., & Turc, A. (2022). Electric Motor Vibrations Dataset. [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.6473455
Source metadata: Zenodo (2022) · DOI: 10.5281/zenodo.6473455
Indexed by IoTDataset.com on Jun 06, 2026
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