研究方向：列车关键部件状态监测与检测；旋转机械故障诊断与状态识别；列车关键部件损伤判别

主持项目：

1.   2023.01-2026.12 国家自然科学基金面上基金 A类 多源耦合激励下高铁车轮-轴箱轴承复合故障解耦与损伤评估研究（52272355） 

2.   2020.01-2022.12国家自然科学基金青年基金 B类 轮对复杂激扰下高铁轴箱轴承故障振动特征提取与演变规律研究（51905453） 

3.   2022.01-2023.12 四川省自然科学基金 高速长距万向轴微弱故障特征提取与服役状态量化评估方法研究（2022NSFSC1918） 

4.   2020.01-2022.12 牵引动力国家重点实验室自主课题 变工况下高铁轴箱轴承故障特征量化表征的强鲁棒统计方法研究（2020TPL-T14）

5.   2020.01-2021.12 中央高校基本科研业务费项目 基于噪声利用的高铁轮对-轴箱轴承复合故障特征增强解耦与辨识研究（2682020CX50） 

6.   2019.11-2022.11中国博士后面上项目 高速列车运行条件下轴箱轴承故障特征量化表征方法研究（2019M663899XB） 

7.   2021.09-2022.09  重载长大列车无线ECP系统列车制动性能研究 R111722H01077国能铁路装备有限责任公司委托项目 横向项目  

8. 2022.05-2023.05  高铁轮对轴承多尺度运维策略与关键技术研究 -- 舍弗勒-西南交通大学开放创新合作基金   横向项目 

发表论文

1. C. Yi*, D. Wang, L. Zhou, et al. Evaluation of the influence of pantograph cracks on contact forces in the interaction between pantograph and catenary. Vehicle System Dynamics, 2022, DOI: 10.1080/00423114.2022.2120023.

2. Cai Yi, Haoxiang Huo, Xiaokang Liao, et al. Investigation on the characterisation of axle box resonance characteristics to wheel excitation, Vehicle System Dynamics, 2022, DOI: 10.1080/00423114.2022.2103437.

3. Cai Yi, Hao Wang, Le Ran, et al. Power spectral density-guided variational mode decomposition for the compound fault diagnosis of rolling bearings, Measurement, 2022, 199, 111494.

4. Cai Yi, Haoxiang Huo, Xiaokang Liao*, et al. Axle box resonance excitation model based on wheelset polygon and its resonance characteristic analysis in high-speed train. Advanced Theory and Simulations, 2022, 已录用.

5. Cai Yi, Le Ran, Jiaying Tang*, et al. An improved sparse representation based on local orthogonal matching pursuit for bearing compound fault diagnosis. IEEE Sensors Journal, 2022, 已录用.

6. 易彩, 林建辉*, 汪浩等. VMD引导的轮对与轴承复合故障诊断方法[J]. 西南交通大学学报, 2022. https://kns.cnki.net/kcms/detail/51.1277.U.20220525.1848.020.html.

7. Cai Yi, Dong Wang*, Lu Zhou, et al. A simulation investigation on the influence of pantograph crack defect on graphite contact strip wear . Engineering Failure Analysis, 2022, 131, 105889.

8. Cai Yi*, Yiqun Li, Xiaoming Huo, Kwok-Leung Tsui. A promising new tool for fault diagnosis of railway wheelset bearings: SSO-based Kurtogram. ISA Transactions, 2022, 128: 498-512.

9.  Q. Zhou, C. Yi*, L. Yan, C. Huang, and J. Lin, “A Blind Deconvolution Approach Based on Spectral Harmonics-to-Noise Ratio for Rotating Machinery Condition Monitoring,” IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2022, p. 16. (Early Access)

10. Xiaokang Liao, Cai Yi, Yi Zhang, Zili Chen, Fengyu Ou, Jianhui Lin. A simulation investigation on the effect of wheel-polygonal wear on dynamic vibration characteristics of the axle-box system, Engineering Failure Analysis, 2022, 139, 106513.

11. 廖小康, 易彩, 张议, 陈滋利, 林建辉. 车轮柔性化对高铁轴箱轴承振动特性分析. 铁道科学与工程学报, 2022. DOI: 10.19713/j.cnki.43-1423/u.T20220078

12. 廖小康, 易彩, 张议, 陈滋利, 林建辉. 车轮扁疤激励下高速列车轴箱系统振动特性研究. 振动、测试与诊断, 2022. (已录用)

13. Q. Zhou, Y. Zhang, C. Yi*, J. Lin, L. He, and Q. Hu, “Convolutional sparse coding using pathfinder algorithm-optimized orthogonal matching pursuit with asymmetric Gaussian chirplet model in bearing fault detection,” IEEE Sensors Journal, pp. 1–1, 2021, doi: 10.1109/JSEN.2021.3086015.

14. Q. Zhou, C. Yi*, C. Huang, and J. Lin, “A Novel Blind Deconvolution Method with Adaptive Period Estimation Technique and Its Application to Fault Feature Enhancement of Bearing,” Shock and Vibration, vol. 2021, pp. 1–24, Nov. 2021, doi: 10.1155/2021/9929306.

15. Liu He, Cai Yi*, Dong Wang. Optimized minimum generalized Lp/Lq deconvolution for recovering repetitive impacts from a vibration mixture. Measurement, 2021, 168, 108329.

16. Xing Zhan, Yi Cai*, Lin Jianhui, et al.        Multi-component fault diagnosis of wheelset-bearing using shift-invariant impulsive dictionary matching pursuit and sparrow search algorithm. Measurement, 2021, 178(4):109375.

17. Liu He, Dong Wang, Cai Yi*, Qiuyang Zhou, Jianhui Lin. Extracting cyclo-stationarity of repetitive transients from envelope spectrum based on prior-unknown blind deconvolution technique. Signal Processing 183(2021):107997.

18. Xiaokang Liao, Cai Yi*, Fengyu Ou, Yi Zhang, Zili Chen, Jianhui Lin, Research on Load Characteristics of Axle-Box Bearing Raceway under Wheel-Rail Excitation, Shock and Vibration, vol. 2021, Article ID 5871667, 13 pages, 2021.

19. Qiuyang Zhou, Cai Yi*, Chenguang Huang, Jianhui Lin, A Novel Blind Deconvolution Method with Adaptive Period Estimation Technique and Its Application to Fault Feature Enhancement of Bearing, Shock and Vibration, vol. 2021, Article ID 9929306, 24 pages, 2021.

20. Shi Ying., Yi Cai*, Lin Jianhui. Ensemble empirical mode decomposition-entropy and feature selection for pantograph fault diagnosis.        Journal of Vibration and Control, 2020:107754632091662.

21. Liu He, Cai Yi*, Jian-hui Lin, et al. Fault detection and behavior analysis of wheelset bearing using adaptive convolutional sparse coding technique combined with bandwidth optimization. Shock and Vibration, 2020, 2020(5):1-27

22. Jin Hang, Lin Jianhui, Chen Xieqi*, Yi Cai*. Modal parameters identification method based on symplectic geometry model decomposition. Shock and Vibration, 2019(12), 1-26.

23. Dong Wang, Yang Zhao, Cai Yi*, Kwok-Leung Tsui, Jianhui Lin. Sparsity guided empirical wavelet transform for fault diagnosis of rolling element bearings. Mechanical Systems and Signal Processing. 2018, 101C: 292-308.

24. Dong Wang, Cai Yi*, Kwok-Leung Tsui, Jianhui Lin. Making EEMD more effective in extracting bearing fault features for intelligent bearing fault diagnosis by using blind fault component separation. Journal of Intelligent & Fuzzy Systems, 2018: 1-13.

25.Cai Yi, Dong Wang, Wei Fan, Kwok-Leung Tsui, Jianhui Lin. EEMD-Based Steady-State Indexes and Their Applications to Condition Monitoring and Fault Diagnosis of Railway Axle Bearings. Sensors. 2018, 18(3): 704.

26.易彩，林建辉，丁建明，张卫华，刘建新. 基于IMF熵价值的轮对轴承故障自适应诊断[J]. 铁道学报. 2017, 39(10): 43-50.

27. Cai Yi, Jianhui Lin, Weihua Zhang, Jianming Ding. Faults Diagnostics of Railway Axle Bearings Based on IMF’s Confidence Index Algorithm for Ensemble EMD. Sensors, 2015, 15(5): 10991-11011.

28. Cai Yi, Jianhui Lin, Tengda Ruan Yanping Li. Real time cardan-shaft state estimation of high-speed train based on Ensemble Empirical Mode Decomposition. Shock and Vibration. 2015（4）: 1~12.

参加国际会议

1. Cai Yi*, Jianhui Lin, Lu Liu, Kwok-Leung Tsui. Quantizing the health state of railway axle bearings with the signal-to-noise ratio defined by the singular value. 2018 IEEE International Conference on Prognostics and Health Management, Seattle, WA, USA, June 11-13, 2018.

2. Study on Vibration Characteristics Analysis and Characterization of Multiple Failure Modes of High-speed Train Axle Bearing        The 11th International Workshop on Structural Health Monitoring, Stanford University, September 12-14, 2017.      

3. Detection of Running Deviation of Cardan Shaft in High-speed Train      The 2017 World Congress on Advances in Structural Engineering and Mechanics ( ASEM17), Aug 28- Sep 1, 2017, KINTEX, Ilsan, Korea.

4. Target Entropy Scale Determination Based on EEMD for Fault Diagnosis of Railway Axle BearingThe 25th International Symposium on Dynamics of Vehicles on Roads and Tracks. Central Queensland University, Queensland, August 14-18, 2017.

5. An Online State Estimation Approach for Railway Axle Bearing Based on EEMD and Entropy   7th IET Conference on Railway Condition Monitoring, 2016: 1-16. EI/国际会议

6. Cai Yi*, Jianhui Lin, Lu Liu. An Online State Estimation Approach for Railway Axle Bearing Based on EEMD and Entropy. 7th IET Conference on Railway Condition Monitoring (RCM 2016), 2016: 1-16.    EI/国际会议

7. Study on Car Body Vibration Transmissibility Analysis Approach for Railway Passenger Carriage   Proceedings of The 2nd International Conference on Mechanic Automation and Control Engineering, 2011: 5281-5284.      EI/国际会议

8. Cai Yi, Jianhui Lin*, Tengda Ruan, et al. CRH5 Cardan Shaft Condition Estimation from Gearbox Vibration. The Second International Conference on Railway  Technology: Research, Development and Maintenance (Railways 2014), Ajaccio, Corsica, France.

9. Research on Vibration Characteristics of Defective Gearbox of High-speed EMU Based on Hilbert-Huang Transform   The 23rd International Symposium on Dynamics of Vehicles on Roads and Tracks (the 23rd IAVSD), Qingdao, China.