Name：Yi Qin
Birthday：08/08/1982
Degree：Ph.D
Professional title：Professor/PHD Advisor
e-mail：qy_808@cqu.edu.cn
Individual Resume
Yi Qin received the B.S. and Ph.D. degrees in mechatronical engineering from Chongqing University, Chongqing, China, in 2004, and 2008, respectively. Since 2009, he has been with the College of Mechanical and Vehicle Engineering and State Key Laboratory of Mechanical Transmission at Chongqing University, Chongqing, China, where he is currently a Professor. He is the Young top-notch talent of China and the Young top-notch talent of Chongqing. He is also selected as World’s Top 2% Scientists 2022 by Stanford University and Elsevier. His current research interests are in the area of intelligent mechanical fault diagnosis and prognosis, intelligent unmanned system, mechanical dynamics and digital twin, intelligent operation and maintenance. He has undertaken a number of national and ministerial projects, such as National Key R&D Program of China, National Natural Science Foundation of China, Chongqing Research Program of Basic Research and Frontier Technology, et al. He has published over 130 papers in IEEE Transactions on Industrial Cybernetics, IEEE Transactions on Industrial Electronics, IEEE Transactions on Industrial Informatics, IEEE/ASME Transactions on Mechatronics, Mechanical Systems and Signal Processing, Mechanism and Machine Theory, Measurement, et al., which are cited by over 3000 times. He has got 18 national invention patents, 2 first prize of science and technology progress of the Ministry of education and 2 first prize of Chongqing Science and technology progress. He is an Editor of Sensors, Shock and Vibration, and Machines, and an editorial board member of Journal of Vibration, Measurement and Diagnosis, and Mechanical Engineering Science. He is the peer reviewer of over 50 journals. He is the senior member of IEEE and the vice chair of IEEE Reliability Society Chongqing Chapter.
Selected Publications
[1] Yi Qin*, Quan Qian, Jun Luo, Huayan Pu. Deep joint distribution alignment: a novel enhanced domain adaptation mechanism for fault transfer diagnosis. IEEE Transactions on Cybernetics, 2022, DOI 10.1109/TCYB.2022.3162957
[2] Jianghong Zhou, Yi Qin*, Jun Luo, Shilong Wang, Tao Zhu. Dual-thread gated recurrent unit for gear remaining useful life prediction. IEEE Transactions on Industrial Informatics, 2022, DOI 10.1109/TII.2022.3217758
[3] Jianghong Zhou, Yi Qin*, Jun Luo, Tao Zhu. Remaining useful life prediction by distribution contact ratio health indicator and consolidated memory GRU. IEEE Transactions on Industrial Informatics, 2022, DOI 10.1109/TII.2022.3218665
[4] Yi Qin*, Quan Qian**, Yi Wang, Jianghong Zhou. Intermediate distribution alignment and its application into mechanical fault transfer diagnosis. IEEE Transactions on Industrial Informatics, 2022, 18(10): 7305-7315.
[5] Sheng Xiang, Yi Qin*, Jun Luo, Huayan Pu. Spatiotemporally multi-differential processing deep neural network and its application to equipment remaining useful life prediction. IEEE Transactions on Industrial Informatics, 2022, 18(10): 7230-7239.
[6] Yangyang Wang, Yi Qin*, Xihou Chen**, Qifu Tang, Tianheng Zhang, Liang Wu. Absolute inductive angular displacement sensor for position detection of YRT turntable bearing. IEEE Transactions on Industrial Electronics, 2022, 69(10): 10644-10655.
[7] Yi Qin*, Xingguo Wu, Jun Luo. Data-model combined driven digital twin of life-cycle rolling bearing. IEEE Transactions on Industrial Informatics, 2022, 18(3): 1530-1540.
[8] Yi Qin*, Jianghong Zhou, Dingliang Chen. Unsupervised health indicator construction by a novel degradation-trend-constrained variational autoencoder and its applications. IEEE/ASME Transactions on Mechatronics, 2022, 27(3): 1447-1456.
[9] Dingliang Chen, Yi Qin*, Jun Luo, Sheng Xiang. Gated adaptive hierarchical attention unit neural networks for the life prediction of servo motors. IEEE Transactions on Industrial Electronics, 2022, 69(9): 9451-9461.
[10] Yi Qin*, Xin Wang, Quan Qian, Huayan Pu, Jun Luo. Multi-scale transfer voting mechanism: a new strategy for domain adaption. IEEE Transactions on Industrial Informatics, 2021, 17(10): 7103-7113.
[11] Yi Qin∗, Dingliang Chen, Sheng Xiang, Caichao Zhu. Gated dual attention unit neural networks for remaining useful life prediction of rolling bearings. IEEE Transactions on Industrial Informatics, 2021, 17(9): 6438-6447.
[12] Yi Qin∗, Sheng Xiang, Yi Chai, Haizhou Chen. Macroscopic-microscopic attention in LSTM networks based on fusion features for gear remaining life prediction. IEEE Transactions on Industrial Electronics, 2020, 67(12): 10865-10875.
[13] Yi Qin*, Jingqiang Zou, Baoping Tang, Yi Wang, Haizhou Chen. Transient feature extraction by the improved orthogonal matching pursuit and K-SVD algorithm with adaptive transient dictionary, IEEE Transactions on Industrial Informatics, 2020, 16(1): 215-227
[14] Yi Qin*, Yongfang Mao, Baoping Tang, Yi Wang, Haizhou Chen. M-band flexible wavelet transform and its application to the fault diagnosis of planetary gear transmission systems. Mechanical Systems and Signal Processing, 2019, 134: 106298.
[15] Yi Qin*, Xin Wang, Jingqiang Zou. The optimized deep belief networks with improved logistic Sigmoid units and their application in fault diagnosis for planetary gearboxes of wind turbines. IEEE Transactions on Industrial Electronics, 2019, 66(5): 3814-3824.
[16] Yi Qin*. A new family of model-based impulsive wavelets and their sparse representation for rolling bearing fault diagnosis. IEEE Transactions on Industrial Electronics, 2018, 65(3): 2716-2726.
[17] Yi Qin*, Zhiwen Wang, Dejun Xi. Tree CycleGAN with maximum diversity loss for image augmentation and its application into gear pitting detection. Applied Soft Computing, 2022, 144: 108130.