不同气候和工况下内燃机主滑动轴承振动数据集。

IF 1 Q3 MULTIDISCIPLINARY SCIENCES
Muhammad Noman Riaz , Amir Hamza , Hamid Jabbar , Manzar Abbas , Mohsin Islam Tiwana
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引用次数: 0

摘要

该数据集包括内燃机正常和故障主轴颈轴承的振动特征,由安装在轴承外壳上的三轴加速度计捕获。发动机暴露在各种气候和操作条件下,包括温度和湿度的变化,并在不同的发动机转速下进行测试,遵循MIL-STD-810G标准。这些数据是在最先进的气候和振动室中收集的,以模拟现实世界的环境条件。该数据集包括500多个文件,每个文件都记录在一系列气候和操作条件下,包括均方根(RMS)值。该数据集为研究人员和从业者提供了一个有价值和可靠的基准,以验证他们的诊断算法和模型是否符合真实的发动机条件,因为没有这样的数据集公开可用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vibration dataset of main journal bearings in internal combustion engines under diverse climatic and varying operating conditions
The dataset includes vibration signatures from both healthy and faulty main journal bearings of an internal combustion engine, captured with a tri-axial accelerometer mounted on the bearings' housing. The engine was exposed to various climatic and operating conditions, including variations in temperature and humidity, and tested at different engine rotation speeds, following a standard, MIL-STD-810G. The data was collected in a state-of-the-art climatic and vibration chamber to simulate real-world environmental conditions. The dataset comprises more than 500 files, each recorded under a range of climatic and operational conditions, with root mean square (RMS) values included. This dataset provides a valuable and reliable benchmark for researchers and practitioners to validate their diagnostic algorithms and models against real engine conditions, as no such dataset is publicly available.
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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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