Rolling-element bearing vibration datasets under varying loads and speeds: A study from Vishwakarma Institute of Technology

IF 1 Q3 MULTIDISCIPLINARY SCIENCES
Yasser N. Aldeoes , Pratibha Mahajan , Shilpa Y. Sondkar , Jitendra A. Gaikwad
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引用次数: 0

Abstract

Data collection and analysis are critical for identifying and diagnosing issues in rolling-element bearings. Vishwakarma Technologies, Pune, India, has developed a unique rolling-element vibration dataset specifically gathered under controlled static load and motion conditions, adding significant value to existing public datasets. This dataset offers researchers precise vibration data that complements existing features, enabling accurate assessments of bearing conditions. Collected using accelerometers, the dataset also provides insights into bearing deterioration under sustained loads, which can help predict failures and support the development of advanced diagnostic tools. The dataset comprises 50 files that cover a wide range of operating and fault conditions, including varying motor speeds, high-loading scenarios, and both healthy and faulty bearing states. It delivers detailed, high-quality information that enhances the detection and diagnosis of rolling-element bearing problems, contributing to more reliable maintenance practices and improved system reliability.
不同载荷和速度下的滚动轴承振动数据集:Vishwakarma 技术学院的一项研究
数据收集和分析是识别和诊断滚动轴承问题的关键。位于印度浦那的Vishwakarma技术公司开发了一个独特的滚动元件振动数据集,专门在受控静载荷和运动条件下收集,为现有的公共数据集增加了重要价值。该数据集为研究人员提供了精确的振动数据,补充了现有功能,从而能够准确评估轴承状况。使用加速度计收集的数据集还可以深入了解轴承在持续载荷下的劣化情况,有助于预测故障并支持先进诊断工具的开发。该数据集包括50个文件,涵盖了广泛的运行和故障条件,包括不同的电机转速,高负载场景,以及健康和故障轴承状态。它提供了详细的、高质量的信息,增强了对滚动轴承问题的检测和诊断,有助于更可靠的维护实践和提高系统可靠性。
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来源期刊
Data in Brief
Data in Brief MULTIDISCIPLINARY SCIENCES-
CiteScore
3.10
自引率
0.00%
发文量
996
审稿时长
70 days
期刊介绍: Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.
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