Language : English
Jingsong Xie
  • Personal Information

    Associate Professor


    Supervisor of Doctorate Candidates


    Supervisor of Master's Candidates

    Date of Employment:2019-06-17

    School/Department:Traffic and Transportation Engineering

    Education Level:Postgraduate (Doctoral)

    Business Address:交通楼412

    Sex:Male

    Contact Information:湖南省长沙市韶山南路铁道学院交通楼

    Degree:Doctoral degree

    Status:Employed

    Alma Mater:西安交通大学

    Discipline:Transportation Engineering
    Mechanical Engineering

  • Profile


    谢劲松

    中南大学 交通运输工程学院 硕士生导师

    邮箱:jingsongxie@foxmail.com

    电话:18008400882

     



    一、个人简介

    近年来,主持国家级纵向课题3项,省部级纵向课题4项,横向课题多项;参与科技部、国家自然科学基金、国家铁路集团、企业委托合作项目等20余项;发表SCI、EI期刊论文40余篇,专利20余项。

    团队简介:

    中南大学交通运输工程学院PHM课题组,经费充足,气氛活泼(现指导研究生12人、博士生10人);

    指导本科生获优秀大学创新创业项目(省级),美国大学生数学建模竞赛(H奖)等奖励;

    指导优秀本-博计划学生(2人),本科阶段发表SCI期刊论文4篇,参加国际/国内学术会5次,优秀会议论文2篇,获国家奖学金、小米特等奖学金(全校本科生5人),为对科研感兴趣的本科生提供施展才华的平台。


    二、教育经历:

    2015-03 至 2018-12, 西安交通大学, 机械工程, 博士

    2013-09 至 2015-02, 西安交通大学, 机械制造及其自动化, 其他

    2009-09 至 2013-07, 西北工业大学, 飞行器制造工程, 学士

     

    三、研究领域:

    交通装备和基础设施健康监测;高铁大数据;机器学习、深度学习;数字孪生;


     

    四、研究方向:

    (1) 基于深度学习的故障诊断

    (2) 基于深度学习的寿命预测

    (3) 齿轮-轴承转子系统动力学建模和故障仿真

    (4) 车辆系统多体动力学仿真

    (5) 面向智能运维的数字孪生

    (6) 智能数据挖掘与特征提取

    (7) 基于大数据平台的诊断算法开发

    (8) 监测诊断软件开发与工程化算法设计

     

     

    五、项目与课题:

     

    (1)      国家自然科学基金委员会,青年基金,高速列车轴箱轴承弱机理驱动深度学习诊断方法研究,2024-01-01至2026-12-31,30万元,在研,主持

    (2)      国家自然科学基金委员会,联合基金,极端环境下时速400公里及以上高速列车动力学行为、安全控制及监测诊断方法研究,2025-01-01至2028-12-31,50万元,在研,单位负责人

    (3)      中华人民共和国科学技术部,重点研发计划,高原密集隧道群对牵引系统空气冷却流场的影响规律及牵引变压器健康状态管理研究,2023-12-07至2026-11-30,50万元,在研,子课题负责人

    (4)      国家国防科工局,技术基础,**伺服机构可靠性仿真,2021-01-01至2023-12-31,130万元,在研,主持

    (5)      中国运载火箭技术研究院,军工纵向,面向流程的 XX 贮存安全性仿真分析技术研究,2023-02-01至2023-12-31,120万元,在研,主持

    (6)      湖南省自然科学基金委员会,青年基金,动车组转向架关键旋转部件高稳健、多尺度故障预警,2021-01-01至2023-12-31,5万元,在研,主持

    (7)      中车企业横向,下一代高速智能动车组智能运维技术研究项目动车组关键系统PHM模型验证测试,2023-10-01至2025-6-30,268万,在研,主持

    (8)   中车企业横向,典型吊挂螺栓的服役性能与修程优化评估技术研究,2021-10-01至2022-12-31,85万元,结题,主持

    (9)   中国运载火箭技术研究院,军工横向,面向群组协同的装备体系弹性机理和弹性设计方法研究, 2021-10-01至2021-12-31,35万元,结题,主持

    (10)   牵引动力国家重点实验室,国家重点实验室开放课题,钢轨损伤的超声导波高分辨率可视化识别方法研究,2021-01-01至2022-12-31,10万元,结题,主持

    (11)   极端服役性能精准制造全国重点实验室,国家重点实验室开放课题,2025-01-01至2026-12-31,5万元,在研,主持

    (12)   先进轨道交通自主运行全国重点实验室, 国家重点实验室开放课题,轴箱轴承数字孪生追踪建模与故障诊断方法研究,2025-01-01至2026-12-31,6万元,在研,主持

    (13)   中南大学教育教学改革研究项目,一般项目,基于职业生涯规划发展的“本研贯通”人才培养模式探究主持,2024-11-01 至 2026-6-30,1万元,在研,主持

    (14)   中南大学教育教学改革研究项目,一般项目,新冠疫情影响下轨道交通装备生产工艺实习虚实交互教学模式研究,2022-06-01 至 2024-5-31,1万元,结题,主持


    六、期刊论文(一作/通讯)

    (1)    A Deep Transfer Learning-Based Open Scenario Diagnostic Framework for Rail Damage Using Ultrasound Guided Waves, IEEE Transactions on Instrumentation and Measurement, 2024, JCR Q1

    (2)      Bearing fault diagnostic framework under unknown working conditions based on condition-guided diffusion model, Measurement, 2024, JCR Q1

    (3)      A simulated-to-real transfer fault diagnosis method based on prototype clustering subdomain adversarial adaptation network for HST bogie bearing, IEEE Transactions on Instrumentation and Measurement, 2024, JCR Q1

    (4)      A lightweight dual-compression fault diagnosis framework for high-speed train bogie bearing, IEEE Transactions on Instrumentation and Measurement, 2024, JCR Q1

    (5)      Fatigue test and service performance evaluation of high-speed train hanging equipment bolts, Structures, 2024, JCR Q1

    (6)      Deep Adversarial Hybrid Domain-Adaptation Network for Varying Working Conditions Fault Diagnosis of High-Speed Train Bogie, IEEE Transactions on Instrumentation and Measurement, 2023, JCR Q1

    (7)      Multi-Information Fusion Fault Diagnosis of Bogie Bearing Under Small Samples via Unsupervised Representation Alignment Deep Q-Learning, IEEE Transactions on Instrumentation and Measurement, 2023, JCR Q1

    (8)      Self-attention Metric Learning Based on Multi-Scale Feature Fusion for Few-shot Fault Diagnosis, IEEE sensors, 2023, JCR Q1

    (9)      A diagnostic framework with a novel simulation data augmentation method for rail damages based on transfer learning, Structural Health Monitoring, 2023, JCR Q1

    (10)   Simulation and experimental study on contact pressure distribution of contact interface in single and double bolted connection structuresJournal of Low Frequency Noise, Vibration & Active Control, 2023 JCR Q1

    (11)   Depth Prototype Clustering Method Based on Unsupervised Field Alignment for Bearing Fault Identification of Mechanical Equipment, IEEE Transactions on Instrumentation and Measurement, 2022, JCR Q1

    (12)   Blade damage monitoring method base on frequency domain statistical index of shaft's random vibration, Mechanical Systems & Signal Processing, 2022, JCR Q1

    (13)   An identification method for excitation location and its application in faults location, Mechanical Systems & Signal Processing, 2022, JCR Q1

    (14)   A novel bearing fault classification method based on XGBoost: The fusion of deep learning-based features and empirical feature, IEEE Transactions on Instrumentation and Measurement, 2021, JCR Q1

    (15)   Meta-learning as a promising approach for few-shot cross-domain fault diagnosis: Algorithms, applications, and prospects, Knowledge-Based Systems, 2021, JCR Q1

    (16)   An efficient method for vibration equations with time varying coefficients and nonlinearitiesJournal of Low Frequency Noise, Vibration & Active Control, 2021, JCR Q1

    (17)   Mechanism explanation and experimental verification of a new modulation frequency characteristic in a disturbed crack rotor, Nonlinear Dynamics, 2019, JCR Q1

    (18)   A new concept of instantaneous whirling speed for cracked rotor’s axis orbit, Applied Sciences, 2019, JCR Q1

    (19)   A novel vibration modeling method for a rotating blade with breathing cracks, SCIENCE CHINA Technological Sciences, 2019, JCR Q1

    (20)   A novel bearing fault diagnosis method under small samples using time-frequency multi-scale convolution layer and hybrid attention mechanism module, Measurement Science and Technology, 2023, JCR Q1

    (21)   A Small Sample Diagnosis Method Driven by Simulation and Test Data: Applied to Axle Box Bearings of High-speed Train, Measurement Science and Technology, 2023, JCR Q1

    (22)   Phase-based spectrum analysis method for identifying weak harmonics, Journal of Vibration and Control, 2018, JCR Q2

    (23)   A Mechanism-Based Automatic Fault Diagnosis Method for Gearboxes, Sensors, 2022, JCR Q2

    (24)   Defect Detection inside a Rail Head by Ultrasonic Guided Waves, Symmetry, 2022, JCR Q2 

    (25)   An outlier cleaning based adaptive recognition method for degradation stage of bearings, Sensors, 2022, JCR Q2

    (26)   Modified breathing mechanism model and phase waterfall plot diagnostic method for cracked rotors, Journal of Mechanical Science and Technology, 2018, JCR Q3

    (27)   磨损水润滑橡胶轴承承载特性研究, 振动与冲击, 2020, EI

    (28)   转向架齿轮箱动力学建模与故障量化分类方法研究,中南大学学报, 2023, EI 

     

    七、授权发明专利 

    (1) 谢劲松;王田天;阳劲松;唐昀昭;李逾严;杨布尧;田龙祯;一种基于波峰计数的齿轮故障量化诊断方法,2022-8-31,中国, ZL202211064515.9

    (2) 谢劲松;谢雨洁;肖友刚;韩锟;少测点工况下列车车轴裂纹定位方法,2021-7-6,中国, ZL201910888486.X

    (3) 谢劲松;谢雨洁;肖友刚;韩锟;一种频谱校正方法,2021-12-24,中国,ZL201910888489.3

    (4) 王田天; 谢劲松; 阳劲松; 郭志斌; 杨布尧; 田龙祯; 李逾严; 一种导波信号的多样性扩充方法、系统、设备及介质,2024-12-01,中国, ZL202211055536.4

    (5) 王田天;谢劲松;阳劲松;杨布尧;张小振;一种多振源系统的故障诊断系统及方法,2022-08-09,中国,ZL202111230641.2

    (6) 訾艳阳;谢劲松;成玮;陈景龙;王宇;杨飞;一种非重力占优裂纹转子刚度呼吸函数计算方法,2018-12-7,中国,ZL201610279678.7

    (7) 訾艳阳;谢劲松;成玮;陈景龙;王宇;杨飞;基于增强相位瀑布图的转子裂纹微弱分数谐波特征识别方法,2018-10-30,中国,ZL201610279679.1

    (8) 阳劲松;王田天;谢劲松;张小振;田龙桢;李先钧;王钦民;基于光纤布拉格光栅的裂纹诊断方法、系统及存储介质,2022-12-27,中国,ZL202210544130.6

    (9) 成玮;褚亚鹏;訾艳阳;陆建涛;曹宏瑞;谢劲松;基于盲源分离技术的运行工况传递路径分析方法,2019-12-24,中国,ZL201611130180.0


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  • Education Background

    [1]  2009.9- 2013.7
    西北工业大学 | University graduated
    [2]  2015.3- 2018.12
    西安交通大学 | With Certificate of Graduation for Doctorate Study
    [3]  2015.3- 2018.12
    西安交通大学 | With Certificate of Graduation for Doctorate Study | Doctoral Degree in Engineering
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  • Research Group

    Name of Research Group:交通院PHM课题组

    Description of Research Group:交通院PHM课题组旨在通过人工智能方法、高精度建模方法来解决高速列车关键部件的寿命预测、故障诊断等PHM问题。通过培养中南大学对人工智能方法、数字信号处理、机械系统建模感兴趣的本科生,完成系统性科学研究。目前课题组拥有"本博计划"学生2名,工程博士1名,24级研究生3名,20级、21级、22级本科生15名。

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