University of Ottawa constant load and speed rolling-element bearing vibration and acoustic fault signature datasets.

ABSTRACT: The collection and analysis of data play a critical role in detecting and diagnosing faults in bearings. However, the availability of large open-access rolling-element bearing datasets for fault diagnosis is limited. To overcome this challenge, the University of Ottawa Rolling-element Bearing Vibration and Acoustic Fault Signature Datasets Operating under Constant Load and Speed Conditions are introduced to provide supplementary data that can be combined or merged with existing bearing datasets to increase the amount of data available to researchers. This data utilizes various sensors such as an accelerometer, a microphone, a load cell, a hall effect sensor, and thermocouples to gather quality data on bearing health. By incorporating vibration and acoustic signals, the datasets enable both

SUBMITTER: Sehri M 

PROVIDER: S-EPMC10331275 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature