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The following bibliography contains all publications indexed in this database that are linked with this name as either author, editor or any other kind of contributor.

  1. Zhao, Xiaoli / Hu, Yuanhao / Liu, Jiahui / Yao, Jianyong / Deng, Wenxiang / Hu, Jian / Zhao, Zhuanzhe / Yan, Xiaoan: A novel intelligent multicross domain fault diagnosis of servo motor-bearing system based on Domain Generalized Graph Convolution Autoencoder. In: Structural Health Monitoring.

    https://doi.org/10.1177/14759217241262722

  2. Ye, Maoyou / Yan, Xiaoan / Chen, Ning / Liu, Ying (2023): A robust multi-scale learning network with quasi-hyperbolic momentum-based Adam optimizer for bearing intelligent fault diagnosis under sample imbalance scenarios and strong noise environment. In: Structural Health Monitoring, v. 23, n. 3 (September 2023).

    https://doi.org/10.1177/14759217231192363

  3. She, Daoming / Chen, Jin / Yan, Xiaoan / Zhao, Xiaoli / Pecht, Michael (2023): Diversity maximization-based transfer diagnosis approach of rotating machinery. In: Structural Health Monitoring, v. 23, n. 1 (May 2023).

    https://doi.org/10.1177/14759217231164921

  4. Yan, Xiaoan / Yan, Wangji / Yuen, Ka-Veng / Yang, Zhixin / Wang, Xianbo (2022): An adaptive variational mode extraction method based on multi-domain and multi-objective optimization for bearing fault diagnosis. In: Structural Health Monitoring, v. 22, n. 4 (December 2022).

    https://doi.org/10.1177/14759217221133283

  5. Yan, Xiaoan / Liu, Ying / Huang, Dongsheng / Jia, Minping (2021): A new approach to health condition identification of rolling bearing using hierarchical dispersion entropy and improved Laplacian score. In: Structural Health Monitoring, v. 20, n. 3 (January 2021).

    https://doi.org/10.1177/1475921720948620

  6. Yan, Xiaoan / Liu, Ying / Jia, Minping (2019): Health condition identification for rolling bearing using a multi-domain indicator-based optimized stacked denoising autoencoder. In: Structural Health Monitoring, v. 19, n. 5 (October 2019).

    https://doi.org/10.1177/1475921719893594

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