遇见数据集

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

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DataCite Commons2025-05-01 更新2025-05-17 收录
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--Contact email: m.najafi@nit.ac.ir --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.

-- 联系邮箱:m.najafi@nit.ac.ir -- 巴布勒诺希尔瓦尼理工大学(Babol Noshirvani University of Technology,简称BNUT) -- 为开展模型评估工作,本数据集新增40条真实标注(Ground Truth),所有标注均由经过专业培训的人员完成,准确性与可靠性均得到保障。 本数据集为红外热成像专用数据集,聚焦电气设备(尤其是感应电机)的状态监测任务。数据集涵盖人工模拟生成的多种内部故障类型,包括定子绕组短路故障、转子卡滞故障以及冷却风扇故障。所有热成像图像均采集自电机实验室,采集设备为Dali-tech T4/T8型红外热成像相机,采集环境温度为23℃。本数据集已向AI系统开发与测试领域的研究人员公开共享。为尊重巴布勒诺希尔瓦尼理工大学(BNUT)及作者的知识产权,使用本数据集时需引用该数据集页面的数字对象标识符(DOI)及相关论文的DOI。 论文标题:基于热成像与可解释机器学习的电气设备故障诊断——基于一个新发布的数据集 DOI: 10.1109/ICSPIS51611.2020.9349599 本数据集所用相机及配套设备的详细规格参数,可查阅Readme_InductionMotor.pdf文件中的表1、表2与表3。 本研究构建了涵盖三相感应电机11种运行状态的热成像图像数据集。本数据集所用相机及设备的规格信息,同样收录于Readme_InductionMotor.pdf文件的表1、表2与表3中。

提供机构:
Mendeley
创建时间:
2020-11-12
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。
以上内容由遇见数据集搜集并总结生成
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