(1) Wei Zhang; Xiange Tian; Guohai Liu; Hui Liu; A fault diagnosis method for rolling bearings based on improved EEMD and resonance demodulation analysis, Proceedings of INCOME-VI and TEPEN 2021: Performance Engineering and Maintenance Engineering, 2023, 117: 669-682. (2) Xiange Tian; Yongjian Jiang; Chen Liang; Cong Liu; You Ying; Hua Wang; Dahai Zhang; Peng Qian; A Novel Condition Monitoring Method of Wind Turbines Based on GMDH Neural Network, Energies, 2022, 15(18). (3) Silvia Tolo; Xiange Tian; Nils Bausch; Victor Becerra; T.V. Santhosh; Gopika Vinod; Edoardo Patelli; Robust on-line diagnosis tool for the early accident detection in nuclear power plants, Reliability Engineering & System Safety, 2019, 186: 110-119. (4) Peng Qian; Xiange Tian; Lap Yan Joash Lee; Jamil Kanfoud; Tat-Hean Gan; A novel condition monitoring method of wind turbines based on Long Short-Term Memory neural network, Energies, 2019, 12(18). (5) Xiange Tian; James X. Gu; Ibrahim Rehab; Gaballa M. Abdalla; Fengshou Gu; Andrew D. Ball; A robust detector for rolling element bearing condition monitoring based on the modulation signal bispectrum and its performance evaluation against the Kurtogram, Mechanical Systems and Signal Processing, 2018, 100: 167-187. (6) Xiange Tian; Victor Becerra; Nils Bausch; T.V. Santhosh; Gopika Vinod; A study on the robustness of neural network models for predicting the break size in LOCA, Progress in Nuclear Energy, 2018, 109: 12-28. (7) Xiange Tian;Victor Becerra; Nils Bausch; T.V. Santhosh; (2017) A method for measuring the robustness of diagnostic models for predicting the break size during LOCA, In Annual Conference of the Prognostics and Health Management Society. Tampa, FL, USA. | 
