Dynamic Fault Detection Method of Traction Systems in High-Speed Trains Based on Joint Observer
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-9319-2_11
Reference14 articles.
1. Chen, H., Jiang, B., Ding, S., Huang, B.: Data-driven fault diagnosis for traction systems in high-speed trains: a survey, challenges, and perspectives. IEEE Trans. Intell. Transp. Syst. 23(3), 1700–1716 (2022)
2. Cheng, C., Wang, J., Chen, H., Chen, Z., Luo, H., Xie, P.: A review of intelligent fault diagnosis for high-speed trains: qualitative approaches. Entropy 23(1), 1 (2021)
3. Huo, M., Luo, H., Yin, S., Jiang, Y., Kaynak, O.: A novel subspace-aided fault detection approach for the drive systems of rolling mills. IEEE Trans. Control Syst. Technol. 30(4), 1742–1749 (2021)
4. Zhu, J., Hu, T., Jiang, B., Yang, X.: Intelligent bearing fault diagnosis using PCA-DBN framework. Neural Comput. Appl. 23(14), 10773–10781 (2020)
5. Ji, H.: Data-driven sensor fault diagnosis under closed-loop control with slow feature analysis. IEEE Sens. J. 22(24), 24299–24308 (2023)
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