Vibration and current dataset of three-phase permanent magnet synchronous motors with stator faults. Jung, W., Yun, S., Lim, Y., Cheong, S., & Park, Y. Data in Brief, 47:108952, April, 2023. Paper doi abstract bibtex Permanent magnet synchronous motors (PMSM) are widely used in industry applications such as home appliances, manufacturing process, high-speed trains, and electric vehicles. Unexpected faults of PMSM are directly related to the significant losses in the engineered systems. The majority of motor faults are bearing fault (mechanical) and stator fault (electrical). This article reports vibration and driving current dataset of three-phase PMSM with three different motor powers under eight different severities of stator fault. PMSM conditions including normal, inter-coil short circuit fault, and inter-turn short circuit fault in three motors are demonstrated with different powers of 1.0 kW, 1.5 kW and 3.0 kW, respectively. The PMSMs are operated under the same torque load condition and rotating speed. Dataset is acquired using one integrated electronics piezo-electric (IEPE) based accelerometer and three current transformers (CT) with National Instruments (NI) data acquisition (DAQ) board under international organization for standardization standard (ISO 10816-1:1995). Established dataset can be used to verify newly developed state-of-the-art methods for PMSM stator fault diagnosis. Mendeley Data. DOI: 10.17632/rgn5brrgrn.5
@article{jung_vibration_2023,
title = {Vibration and current dataset of three-phase permanent magnet synchronous motors with stator faults},
volume = {47},
issn = {2352-3409},
url = {https://www.sciencedirect.com/science/article/pii/S2352340923000707},
doi = {10.1016/j.dib.2023.108952},
abstract = {Permanent magnet synchronous motors (PMSM) are widely used in industry applications such as home appliances, manufacturing process, high-speed trains, and electric vehicles. Unexpected faults of PMSM are directly related to the significant losses in the engineered systems. The majority of motor faults are bearing fault (mechanical) and stator fault (electrical). This article reports vibration and driving current dataset of three-phase PMSM with three different motor powers under eight different severities of stator fault. PMSM conditions including normal, inter-coil short circuit fault, and inter-turn short circuit fault in three motors are demonstrated with different powers of 1.0 kW, 1.5 kW and 3.0 kW, respectively. The PMSMs are operated under the same torque load condition and rotating speed. Dataset is acquired using one integrated electronics piezo-electric (IEPE) based accelerometer and three current transformers (CT) with National Instruments (NI) data acquisition (DAQ) board under international organization for standardization standard (ISO 10816-1:1995). Established dataset can be used to verify newly developed state-of-the-art methods for PMSM stator fault diagnosis. Mendeley Data. DOI: 10.17632/rgn5brrgrn.5},
urldate = {2023-10-04},
journal = {Data in Brief},
author = {Jung, Wonho and Yun, Sung-Hyun and Lim, Yoon-Seop and Cheong, Sungjin and Park, Yong-Hwa},
month = apr,
year = {2023},
keywords = {Condition Monitoring, Current, Fault Diagnosis, Stator Fault, Three-Phase Permanent Magnet Synchronous Motors, Vibration},
pages = {108952},
}
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This article reports vibration and driving current dataset of three-phase PMSM with three different motor powers under eight different severities of stator fault. PMSM conditions including normal, inter-coil short circuit fault, and inter-turn short circuit fault in three motors are demonstrated with different powers of 1.0 kW, 1.5 kW and 3.0 kW, respectively. The PMSMs are operated under the same torque load condition and rotating speed. Dataset is acquired using one integrated electronics piezo-electric (IEPE) based accelerometer and three current transformers (CT) with National Instruments (NI) data acquisition (DAQ) board under international organization for standardization standard (ISO 10816-1:1995). Established dataset can be used to verify newly developed state-of-the-art methods for PMSM stator fault diagnosis. Mendeley Data. 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