{"id":"42v3s74gf9","doi":{"id":"10.17632/42v3s74gf9.1","status":"allocated","prefix":"10.17632"},"name":"UPATRAS Rotating Machinery Vibration Dataset for Incipient Fault Diagnosis under Varying Rotating Speed","description":"This dataset contains vibration measurements acquired from a rotating machinery test rig developed at the University of Patras, Greece, at the Stochastic Mechanical Systems and Automation (SMSA) Laboratory. The test rig consists of two foot-mounted electric motors coupled via a claw clutch and instrumented with a single uniaxial accelerometer mounted on the drive motor. The dataset has been designed for research on vibration-based condition monitoring, fault detection, fault diagnosis, signal processing, feature extraction, machine learning, deep learning, and related data-driven methodologies for rotating machinery operating under varying speed conditions. In contrast to many rotating machinery datasets that focus on a limited number of operating conditions, the present dataset provides dense coverage of a wide rotating-speed range.\n\nThe dataset comprises eight machinery states, namely one healthy state and seven incipient fault scenarios associated with three fault families: limited unbalance, mechanical looseness, and coupler wear. The limited unbalance scenarios are implemented by replacing the main coupler mounting bolt with a heavier bolt, leading to two fault levels, denoted as Unbalance 3g and Unbalance 5g. The mechanical looseness scenarios are implemented through torque reduction of the drive-motor mounting bolts A and B, leading to four fault cases: Bolt A 50%, Bolt A 100%, Bolt B 50%, and Bolt B 100%. The coupler wear scenario corresponds to incipient wear at the base of a single spider tooth of the claw clutch. The healthy state is characterized by mounting torques [A,B] = [5,5] N m, while the looseness scenarios are defined through the corresponding reduced torque values.\n\nThe measurements are acquired under 75 different rotating speeds ranging from 35.0 Hz to 49.8 Hz with a step of 0.2 Hz. Four measurement sequences are provided for the healthy state and five for each faulty state, leading to a total of 2925 individual vibration signals. Each signal contains 3500 samples, corresponding to 3.42 s with sampling frequency 1024 Hz and frequency bandwidth [0 - 512] Hz. The dataset is provided entirely in CSV format. \n\nIf you use this dataset in your work, please cite the following publication: https://doi.org/10.1016/j.ymssp.2025.113204\n\nFurther details on the data are available in the README.pdf file included in this dataset. 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Note that further permission may be required for any content within the dataset that is identified as belonging to a third party.","url":"http://creativecommons.org/licenses/by/4.0","category":"Creative","short_name":"CC BY 4.0","full_name":"Creative Commons Attribution 4.0 International"},"related_links":[],"funders":[{"identity":"https://ror.org/05v75r592","name":"Hellenic Foundation for Research and Innovation","location":"Athens"}],"customer_id":"7377952c-6404-4428-bbfc-77242cfc301e","modified_on":"2026-04-06T05:51:58.687Z","created_on":"2026-04-05T21:01:50.696Z","confidential":false,"links":{"view":"https://data.mendeley.com/datasets/42v3s74gf9"},"repository":{"id":"MENDELEY_DATA","name":"Mendeley Data"}}