The Squirrel Cage Induction Motor Fault Diagnosis Dataset is a multi-sensor data collection gathered to expand research on anomaly detection, fault diagnosis, and predictive maintenance, mainly using non-invasive methods such as thermal observation or vibration measurement. The measurements were gathered using an advanced Wrocław University of Science and Technology laboratory designed to simulate and study motor defects. The collected dataset is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. Available data: thermal images The example dataset utilization is presented in the GitHub repository: motor-fault-diagnosis Related publications: Unraveling Induction Motor State through Thermal Imaging and Edge Processing: A Step towards Explainable Fault Diagnosis

{"references": ["Piechocki M, Pajchrowski T, Kraft M, Wolkiewicz M, Ewert P. Unraveling Induction Motor State through Thermal Imaging and Edge Processing: A Step towards Explainable Fault Diagnosis. Eksploatacja i Niezawodno\u015b\u0107 \u2013 Maintenance and Reliability. 2023;25(3). https://doi.org/10.17531/ein/170114"]}

Currently, the presented, publicly available dataset consists of thermal images. In further releases related to the publication process, other sensor data (vibrations, current signal, sound) will be added to this repository.