Thermal image of equipment (Induction Motor) + 40 Ground Truths added

--Contact email: [e-mail]
--Babol Noshirvani University of Technology
-- 40 Ground Truths are added to the dataset in order to conduct the evaluation. The annotations have been made by trained personnel and are considered to be accurate and reliable.
This is a thermal image dataset specifically focused on condition monitoring of electrical equipment, specifically induction motors. The dataset includes artificially generated internal faults, such as short circuit failures in the stator windings, stuck rotor faults, and cooling fan failures. The thermal images were acquired using a Dali-tech T4/T8 infrared thermal image camera in an Electrical Machines Laboratory, with an ambient temperature of 23°. This dataset has been made publicly available for use by researchers in the field of AI system development and testing. To respect the rights of BNUT and authors, referencing the page's DOI and related paper DOI is necessary.

paper title: Fault Diagnosis of Electrical Equipment through Thermal Imaging and Interpretable Machine Learning Applied on a Newly-introduced Dataset
DOI: 10.1109/ICSPIS51611.2020.9349599

The specifications of the camera and equipment used to create this dataset are detailed in Tables 1, 2, and 3 in the Readme_InductionMotor.pdf file.
In this work, a dataset of thermographic images representing 11 conditions for 3-Phase induction motors was introduced. Specifications of Camera and equipment used for
this very dataset is shown in tables 1, 2, and 3 in the Readme_InductionMotor.pdf.

搜集汇总

背景与挑战

背景概述

这是一个用于感应电机状态监测的热图像数据集，包含人工生成的内部故障类型（如定子绕组短路、转子卡死和冷却风扇故障），并提供了40个由专业人员标注的真实标注以支持评估。数据集由Dali-tech T4/T8红外热像仪在实验室环境下采集，旨在为AI系统开发和测试提供研究资源，使用需引用相关DOI。