Academic Appointments

  • Research Engineer, Aeronautics and Astronautics

Professional Education

  • PhD, Tsinghua University (2016)

All Publications

  • Effect of multi-stage heat treatment on the microstructure and mechanical properties of Ti-6Al-4V alloy deposited by high-power laser melting deposition MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING Tao, S., Zhi, G., Zhang, Z., Liu, Y., Li, H., Xie, S., Xie, P., Chen, H. 2024; 895
  • Study on the Forming Process and Properties of AlSi60 Alloy by Selective Laser Melting COATINGS Li, G., Zhi, G., He, Y., Zhang, Z., Chen, Y., Rong, P., Ma, S., Xie, P., Chen, H. 2024; 14 (3)
  • A Reversible Residual Network-Aided Canonical Correlation Analysis to Fault Detection and Diagnosis in Electrical Drive Systems IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT Wang, S., Ju, Y., Fu, C., Xie, P., Cheng, C. 2024; 73
  • Fault detection using generalized autoencoder with neighborhood restriction for electrical drive systems of high-speed trains CONTROL ENGINEERING PRACTICE Wang, S., Jub, Y., Xie, P., Cheng, C. 2024; 143
  • Numerical simulation and mechanism analysis of thermal fatigue crack for low-alloy steel brake disc of high-speed train INTERNATIONAL JOURNAL OF RAIL TRANSPORTATION Wang, J., Zafar, M., Chen, Y., Zuo, L., Zhang, X., Xie, P., Zhao, H. 2023
  • Machine Learning-Based Prediction of Mechanical Properties and Performance of Nickel-Graphene Nanocomposites Using Molecular Dynamics Simulation Data ACS APPLIED NANO MATERIALS Jin, W., Pei, J., Xie, P., Chen, J., Zhao, H. 2023; 6 (13): 12190-12199
  • A Novel Data-Driven Fault Detection Method Based on Stable Kernel Representation for Dynamic Systems. Sensors (Basel, Switzerland) Wang, Q., Peng, B., Xie, P., Cheng, C. 2023; 23 (13)


    With the steady improvement of advanced manufacturing processes and big data technologies, modern industrial systems have become large-scale. To enhance the sensitivity of fault detection (FD) and overcome the drawbacks of the centralized FD framework in dynamic systems, a new data-driven FD method based on Hellinger distance and subspace techniques is proposed for dynamic systems. Specifically, the proposed approach uses only system input/output data collected via sensor networks, and the distributed residual signals can be generated directly through the stable kernel representation of the process. Based on this, each sensor node can obtain the identical residual signal and test statistic through the average consensus algorithms. In addition, this paper integrates the Hellinger distance into the residual signal analysis for improving the FD performance. Finally, the effectiveness and accuracy of the proposed method have been verified in a real multiphase flow facility.

    View details for DOI 10.3390/s23135891

    View details for PubMedID 37447748

  • Surface morphologies of intra-layer printing process in electron beam powder bed fusion: A high-fidelity modeling study with experimental validation ADDITIVE MANUFACTURING Wu, C., Zhao, H., Li, Y., Xie, P., Lin, F. 2023; 72
  • Key Parameters and Optimal Design of a Split Induction Coil for T-Shaped Pipe Brazing COATINGS Zhang, Z., Yang, Z., Xie, P., Zhao, Y., Shan, J., Liu, Y., Wu, A., Ma, S., Zhang, L., Chen, H. 2023; 13 (5)
  • Slow feature analysis-aided detection and diagnosis of incipient faults for running gear systems of high-speed trains ISA TRANSACTIONS Cheng, C., Liu, M., Chen, H., Xie, P., Zhou, Y. 2022; 125: 415-425


    Incipient faults in running gear systems corrupt the overall performance of high-speed trains, increasing the necessity of fault detection and diagnosis whose purpose is to maintain the safe and stable operation of high-speed trains. For this purpose, a novel data-driven method, that utilizes Hellinger distance and slow feature analysis, is proposed in this study. By integrating Hellinger distance into slow feature analysis, a new test statistic is defined for detecting incipient faults in running gear systems. Furthermore, the hidden Markov method is developed for performing reliable fault diagnosis tasks. The salient strengths of the proposed method lie in its satisfactory fault detectability on the one hand and the considerable robustness against high-level noises on the other hand. Finally, the effectiveness of the proposed method is verified through a numerical example and a running gear system of high-speed trains under actual working conditions.

    View details for DOI 10.1016/j.isatra.2021.06.023

    View details for Web of Science ID 000830058600015

    View details for PubMedID 34187683

  • A Review of Intelligent Fault Diagnosis for High-Speed Trains: Qualitative Approaches ENTROPY Cheng, C., Wang, J., Chen, H., Chen, Z., Luo, H., Xie, P. 2021; 23 (1)


    For ensuring the safety and reliability of high-speed trains, fault diagnosis (FD) technique plays an important role. Benefiting from the rapid developments of artificial intelligence, intelligent FD (IFD) strategies have obtained much attention in the field of academics and applications, where the qualitative approach is an important branch. Therefore, this survey will present a comprehensive review of these qualitative approaches from both theoretical and practical aspects. The primary task of this paper is to review the current development of these qualitative IFD techniques and then to present some of the latest results. Another major focus of our research is to introduce the background of high-speed trains, like the composition of the core subsystems, system structure, etc., based on which it becomes convenient for researchers to extract the diagnostic knowledge of high-speed trains, where the purpose is to understand how to use these types of knowledge. By reasonable utilization of the knowledge, it is hopeful to address various challenges caused by the coupling among subsystems of high-speed trains. Furthermore, future research trends for qualitative IFD approaches are also presented.

    View details for DOI 10.3390/e23010001

    View details for Web of Science ID 000610140400001

    View details for PubMedID 33374991

    View details for PubMedCentralID PMC7822053

  • A Novel Fault Detection Method for Running Gear Systems Based on Dynamic Inner Slow Feature Analysis IEEE ACCESS Song, Y., Yang, S., Cheng, C., Xie, P. 2020; 8: 211371-211379
  • Residual Stress, Microstructure and Mechanical Properties in Thick 6005A-T6 Aluminium Alloy Friction Stir Welds METALS Liu, X., Xie, P., Wimpory, R., Li, W., Lai, R., Li, M., Chen, D., Liu, Y., Zhao, H. 2019; 9 (7)

    View details for DOI 10.3390/met9070803

    View details for Web of Science ID 000482332400087

  • Evaluation on Residual Stresses in Thick Titanium Welded Alloys Zhao, H., Xie, P., Shabadi, R., Ionescu, M., Jeandin, M., Richard, C., Chandra, T. TRANS TECH PUBLICATIONS LTD. 2018: 1095-1098
  • Measuring residual stresses in linear friction welded joints composed by dissimilar titanium SCIENCE AND TECHNOLOGY OF WELDING AND JOINING Xie, P., Zhao, H., Liu, Y. 2016; 21 (5): 351-357
  • Evaluation of Residual Stresses Relaxation by Post Weld Heat Treatment Using Contour Method and X-ray Diffraction Method EXPERIMENTAL MECHANICS Xie, P., Zhao, H., Wu, B., Gong, S. 2015; 55 (7): 1329-1337
  • Using Finite Element and Contour Method to Evaluate Residual Stress in Thick Ti-6Al-4V Alloy Welded by Electron Beam Welding ACTA METALLURGICA SINICA-ENGLISH LETTERS Xie, P., Zhao, H., Wu, B., Gong, S. 2015; 28 (7): 922-930
  • Simulation Study on the Dynamic Roll Response of a Partially-Filled Liquid Tank Vehicles Li Song, Jiang Liyong, Zong Changfu, Qin Shuo, Xie Pu, Song Limin, IEEE IEEE. 2012
  • Research on Algorithm of Stability Control for Tractor Semi-trailer Mai, L., Xie, P., Zong, C., Guo, S., Fukuda, T., Yo, Y., Yu, H. IEEE. 2009: 4224-+