Thermal Images of Induction Motor

Dataset Overview

Collected at the Electrical Machines Laboratory at Babol Noshirvani University of Technology, this dataset encompasses 11 operational conditions of induction motors, including:

• 8 short circuit failures in stator windings
• Stuck rotor fault
• Cooling fan failure

Key Features

1. High-Quality Thermal Imaging: Data captured with the advanced Dali-tech T4/T8 infrared camera ensures precision.
2. Wide Range of Faults: Includes diverse internal faults to facilitate comprehensive fault diagnosis research.
3. Artificially Generated Faults: Focuses on internal faults, excluding external components or setup failures, ensuring controlled testing conditions.
4. Publicly Available for Researchers: This dataset is accessible for use in AI model development and fault detection studies, with proper citation of the source.

Applications

This dataset is ideal for:

• AI-Powered Fault Diagnosis: Train machine learning and deep learning models to detect and classify faults in induction motors.
• Predictive Maintenance: Develop systems to predict and mitigate motor failures in industrial applications.
• Thermal Image Analysis: Explore patterns in thermographic data for condition monitoring of electrical equipment.