Paper Publications
- Li Xin, Shao Haidong, Jiang Hongkai, Xiang Jiawei. Modified Gaussian convolutional deep belief network and infrared thermal imaging for intelligent fault diagnosis of rotor-bearing system under time-varying speeds[J]. Structural Health Monitoring, 2021, 21:339-353. (IF= 5.710，Top期刊)
- 李鑫, 杨宇, 程健, 邵海东，程军圣. 基于鲁棒不平衡凸包分类的锥齿轮箱故障诊断方法[J]. 机械工程学报. (网络发表，EI)
- Li Xin, Yang Yu, Pan Haiyang, Cheng Jian, Cheng Junsheng. A novel deep stacking least squares support vector machine for rolling bearing fault diagnosis[J]. Computers in Industry, 2019, 110: 36-47. (IF= 11.245，JCR 1区)
- Li Xin, Li Yong, Yan Ke, Shao Haidong, Janet(Jing) Lin. Intelligent fault diagnosis of bevel gearboxes using semi-supervised probability support matrix machine and infrared imaging[J]. Reliability Engineering & System Safety, 2022: 108921. (IF= 7.247，Top期刊)
- Li Xin, Yang Yu, Wang Ping, Wang Jian, Cheng Junsheng. A bearing fault diagnosis scheme with statistical-enhanced covariance matrix and Riemannian maximum margin flexible convex hull classifier[J]. ISA transactions, 2021, 111: 323-336. (IF= 5.911，Top期刊)
- Li Xin, Cheng Jian, Shao Haidong, Liu Kan, Cai Baoping. A Fusion CWSMM-based Framework for Rotating Machinery Fault Diagnosis under Strong Interference and Imbalanced Case[J]. IEEE Transactions on Industrial Informatics, 2021, 18(8): 5180-5189. (IF= 11.648，ESI高被引论文，Top期刊)
- Li Xin, Yang Yu, Pan Haiyang, Cheng Jian, Cheng Junsheng. Nonparallel least squares support matrix machine for rolling bearing fault diagnosis[J]. Mechanism and Machine Theory, 2020, 145: 103676. (IF= 4.930，Top期刊)
- 李鑫, 程军圣, 吴小伟, 王健, 杨宇. SPCA 和 OCHD 相结合的旋转机械早期微弱故障检测方法[J]. 中国机械工程. (录用, EI)
- Li Xin, Shao Haidong, Lu Siliang, Xiang Jiawei, Cai Baoping. Highly-efficient fault diagnosis of rotating machinery under time-varying speeds using LSISMM and small infrared thermal images[J]. IEEE Transactions on Systems, Man and Cybernetics: Systems, 2022, 52(12): 7328-7340. (IF= 11.471，ESI高被引论文，Top期刊)
- Li Xin, Zhong Xiang, Shao Haidong, Han Te, Shen Changqing. Multi-sensor gearbox fault diagnosis by using feature-fusion covariance matrix and multi-Riemannian kernel ridge regression[J]. Reliability Engineering & System Safety, 2021, 216: 108018. (IF=7.247，Top期刊)