{"id":"cbpr9fvvwb","doi":{"id":"10.17632/cbpr9fvvwb.2","status":"allocated","prefix":"10.17632"},"name":"Vibration dataset of a rotor-shaft test rig (misalignment under load variations)","description":"1. System overview\nThis dataset provides high-resolution vibration signals designed for the development and validation of misalignment detection algorithms in rotating machinery operating under varying load conditions. The experiments were conducted at Poznań University of Technology. The experimental data were collected from a laboratory-scale rotor-shaft test rig consisting of a three-phase electric motor, a gearbox, and a hydraulic gear pump. The gearbox features a transmission system of four identical spur gears - configured as two interacting pairs - with each gear possessing 29 teeth.\nThe simulation of mechanical faults focused on parallel shaft misalignment, which was introduced by precisely adjusting the separation between the two shafts of the gear transmission. The dataset captures five distinct levels of fault severity: a healthy state (0 mm) and four progressive misalignment conditions at 0.25 mm, 0.5 mm, 0.75 mm, and 1.0 mm. These faults are evaluated across a comprehensive range of operational loads to simulate real-world industrial environments. Load variations were achieved by regulating the pressure at the hydraulic gear pump's throttle valve, spanning from 0 MPa to 4.0 MPa in increments of 0.4 MPa. Throughout the testing, the system maintained an average rotational speed of 1490.68 RPM, which corresponds to a fundamental rotational frequency of 25 Hz and a primary gear meshing frequency of 733 Hz.\n2. Data acquisition \nData acquisition was performed using a 24-bit VIBDaq 4+ system at a sampling rate of 11 kHz, with each recording containing 991,232 samples to ensure sufficient data for advanced stationarity and frequency-domain analysis. The vibration signals were recorded from three specific positions to capture the complex dynamics of the transmission system. The third data column contains measurements from acceleration sensor #1, located on the gearbox housing. The fourth data column represents acceleration sensor #2, mounted at the bearing of the input wheel. The fifth data column captures signals from acceleration sensor #3, positioned at the bearing between the gearbox and the pump.\nTo isolate the mechanical vibrations of interest and remove electrical noise, all signals were processed using 10th-order Butterworth filters with a high-pass cutoff of 7 Hz and a low-pass cutoff of 4 kHz. \n3. Acknowledgments\nResearch project “Non-classical methods for misalignment monitoring and detection in rotor-shaft systems under varying load conditions”, funded by the Ministry of Science and Higher Education (MNiSW) of Poland under the Implementation Doctorate Programme – 8th edition (10/2024 – 10/2028), grant number: DWD/8/0069/2024. The project is implemented in collaboration with ABB Business Services sp. z o.o. in Krakow.\nRoman Barczewski acknowledges the recipient of Departmental Research Fund no. 0612/SBAD/3628 for the experimental work undertaken as a part of the research activities at Poznań University of Technology.","version":2,"contributors":[{"institution":{"id":"3c88656c-a741-4876-be19-26862b05521e","name":"Poznań University of Technology","ror_id":"https://ror.org/00p7p3302"},"first_name":"Roman","last_name":"Barczewski","orcid_id":"0000-0002-3715-1182"},{"institution":{"id":"ab38918f-5ba5-4fad-9dad-85858382c03c","name":"AGH University of Krakow","ror_id":"https://ror.org/00bas1c41"},"profile_id":"5546f19a-1df4-48cf-8f73-80b488ec0ab1","first_name":"Sylwester","last_name":"Szewczyk","orcid_id":"0009-0009-2122-2386"},{"institution":{"id":"ab38918f-5ba5-4fad-9dad-85858382c03c","name":"AGH University of Krakow","ror_id":"https://ror.org/00bas1c41"},"first_name":"Wiesław","last_name":"Staszewski","orcid_id":"0000-0003-3071-7427"},{"institution":{"id":"ab38918f-5ba5-4fad-9dad-85858382c03c","name":"AGH University of Krakow","ror_id":"https://ror.org/00bas1c41"},"profile_id":"a5241969-a4d4-4f68-bafa-a930c63a3242","first_name":"Phong","last_name":"Dao","orcid_id":"0000-0002-9211-5619"}],"files":[{"filename":"vibration_dataset_of_rotorshaft_test_rig.rar","id":"bbcdd667-b8df-4220-ba31-2a69f68b5bc0","content_details":{"id":"53d68b23-a309-4d7f-a471-8b81c0c6693f","sha256_hash":"f383347b2c7e27d92e93f5185ce59538f712051fd1151875de7d0b0d44689cad","content_type":"application/octet-stream","size":1027349575,"created_date":"2026-03-10T18:38:05.663Z","download_url":"https://data.mendeley.com/public-files/datasets/cbpr9fvvwb/files/bbcdd667-b8df-4220-ba31-2a69f68b5bc0/file_downloaded","view_url":"https://data.mendeley.com/public-files/datasets/cbpr9fvvwb/files/bbcdd667-b8df-4220-ba31-2a69f68b5bc0/file_viewed","download_expiry_time":"2126-09-15T21:12:42.440415769Z"},"metrics":{"downloads":0,"previews":0},"size":1027349575,"status":"COMPLETED"}],"versions":[{"version":2,"available":true,"publish_date":"2026-09-01T13:42:00.269Z"},{"version":1,"available":true,"publish_date":"2026-03-16T22:23:44.906Z"}],"articles":[],"categories":[{"id":"data.elsevier.com/vocabulary/OmniScience/Concept-253697063","label":"Structural Health Monitoring"},{"id":"data.elsevier.com/vocabulary/OmniScience/Concept-257942051","label":"Vibration Analysis"},{"id":"data.elsevier.com/vocabulary/OmniScience/Concept-601751003","label":"Condition-Based Maintenance"},{"id":"data.elsevier.com/vocabulary/OmniScience/Concept-603585147","label":"Machinery Fault Diagnosis"}],"institutions":[{"id":"3c88656c-a741-4876-be19-26862b05521e","name":"Poznań University of Technology","ror_id":"https://ror.org/00p7p3302"},{"id":"ab38918f-5ba5-4fad-9dad-85858382c03c","name":"AGH University of Krakow","ror_id":"https://ror.org/00bas1c41"}],"metrics":{"views":0,"file_downloads":0,"file_previews":0},"available":true,"method":"Import the dataset file using a data analysis environment such as R, Python, or MATLAB. No preprocessing is required, since the dataset contains no missing, corrupted, or unphysical values. The file names follow the format SIG_DMG_Lxxx_Pxx, where the Lxxx segment identifies the level of parallel shaft misalignment in millimeters (e.g., L075 for 0.75 mm) and the Pxx segment specifies the applied hydraulic load in MPa (e.g., P32 for 3.2 MPa), with both parameters represented as numerical codes that exclude the decimal point","size":1027349575,"owner":{"institution":{"id":"ab38918f-5ba5-4fad-9dad-85858382c03c","name":"AGH University of Krakow","ror_id":"https://ror.org/00bas1c41"},"profile_id":"5546f19a-1df4-48cf-8f73-80b488ec0ab1","first_name":"Sylwester","last_name":"Szewczyk","orcid_id":"0009-0009-2122-2386"},"channel":"WEB","owner_id":"5546f19a-1df4-48cf-8f73-80b488ec0ab1","publish_date":"2026-09-01T13:42:00.269Z","data_licence":{"id":"01d9c749-3c4d-4431-9df3-620b2dcfe144","description":"You can share, copy and modify this dataset so long as you give appropriate credit, provide a link to the CC BY license, and indicate if changes were made, but you may not do so in a way that suggests the rights holder has endorsed you or your use of the dataset. 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":[{"type":"article","rel":"related_to","href":"https://www.mdpi.com/3575822"}],"funders":[{"grant_id":"0612/SBAD/3628","name":"Departmental Research Fund"},{"identity":"https://ror.org/03ha2q922","grant_id":"UMO-2023/51/B/ST8/01253, Non-classical Approaches for Condition Monitoring and Fault Detection of Wind Turbines.","name":"National Science Centre","location":"Krakow"},{"identity":"https://ror.org/05dwvd537","grant_id":"DWD/8/0069/2024, Non-classical methods for misalignment monitoring and detection under varying load conditions. 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