Publisher
Springer Nature Singapore
Reference39 articles.
1. Chu, W., Liu, T., Wang, Z., Liu, C., Zhou, J.: Research on the sparse optimization method of periodic weights and its application in bearing fault diagnosis. Mech. Mach. Theory 177, 105063 (2022)
2. Zhuang, D., et al.: The IBA-ISMO method for rolling bearing fault diagnosis based on VMD-sample entropy. Sensors 23(2), 991 (2023)
3. Gu, H., Liu, W., Zhang, Y., Jiang, X.: A novel fault diagnosis method of wind turbine bearings based on compressed sensing and AlexNet. Measur. Sci. Technol. 33(11), 115011 (2022)
4. Zou, W., Xia, Y., Li, H.: Fault diagnosis of Tennessee-Eastman process using orthogonal incremental extreme learning machine based on driving amount. IEEE Trans. Cybern. 48(12), 3403–3410 (2018)
5. Peng, P., et al.: Progressively balanced supervised contrastive representation learning for long-tailed fault diagnosis. IEEE Trans. Instrum. Meas. 71, 1–12 (2022)