2026-10-14T05:22:21Z https://www.scidb.cn/oai

10.57760/sciencedb.20533 2025-02-08T09:17:23Z

2025-02-08 Data about the classification of superconducting radio-frequency cavity faults of CAFE2 using machine learning doi:10.57760/sciencedb.20533 en This dataset comprises labeled fault data from superconducting radio-frequency (SRF) cavities, including both waveform images and associated operational parameters. The dataset provides examples of various SRF cavity fault patterns and their corresponding classifications. Due to the large volume of collected data, we have selected and uploaded only several representative examples for each fault pattern, ensuring that these samples effectively demonstrate the typical characteristics of each fault type. superconducting radio-frequency cavity; fault recognition; machine learning Lijuan Yang Feng Qiu Yuan He PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset http://www.doi.org/https://doi.org/10.1007/s41365-025-01685-5 Science Data Bank