IMAD-DS: Industrial Multi-Sensor Anomaly Detection Dataset
Abstract
"IMAD-DS captures multi-rate, multi-sensor signals from scaled industrial machines, including a robotic arm and a brushless motor, for anomaly detection research."
Description
Overview
Designed to reflect domain shifts in real industrial environments, this dataset includes normal and abnormal operating conditions under varying settings.
Technical Details
Includes analog microphone data (16 kHz), 3-axis accelerometer (6.7 kHz), and 3-axis gyroscope readings.
Collection Setup
Collected using the STEVAL-STWINBX1 IoT Sensor Industrial Node on scaled industrial equipment.
Recommended Research Tasks
Vibration analysis, acoustic anomaly detection, and sensor fusion for industrial monitoring.
Access & License
Available on Zenodo for open research. Access Dataset
📊 View Data Structure
To explore column names, data types, and sample rows, visit the official dataset page on Kaggle.
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Cite This Dataset
Augusti, F., Albertini, D., Esmer, K., Sannino, R., & Bernardini, A. (2024). IMAD-DS: Industrial Multi-Sensor Anomaly Detection Dataset. [Dataset]. {Zenodo. https://doi.org/10.5281/zenodo.12665499
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Original source: {Zenodo (2024). Visit official page for more details.
Indexed by IoTDataset.com on Feb 05, 2026
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