[1] Hua Li, Tao Liu, Xing Wu, Shaobo Li. Correlated SVD and its application in Bearing Fault Diagnosis[J]. IEEE Transactions on Neural Networks and Learning Systems, 2023, 34(1): 355 - 365.（SCI，中科院一区Top，IF：14.255）
[2]Hua Li, Tao Liu, Xing Wu, Qing Chen. Enhanced Frequency Band Entropy Method for Fault Feature Extraction of Rolling Element Bearings[J]. IEEE Transactions on Industrial Informatics, 2020, 16(9):5780-5791. （SCI，中科院一区Top，IF：11.648）
[3]Hua Li, Tao Liu, Xing Wu, Qing Chen. A bearing fault diagnosis method based on enhanced singular value decomposition[J]. IEEE Transactions on Industrial Informatics, 2021, 17(5): 3220-3230. （SCI，中科院一区Top，IF：11.648）
[4]Hua Li, Xing Wu, Tao Liu, Shaobo Li. The Methodology of Modified Frequency Band Envelope Kurtosis for Bearing fault diagnosis[J]. IEEE Transactions on Industrial Informatics, 2023, 19(3): 2856-2865.（SCI，中科院一区Top，IF：11.648）
[5]Hua Li, Tao Liu, Xing Wu, Qing Chen. Research on bearing fault feature extraction based on singular value decomposition and optimized frequency band entropy[J]. Mechanical Systems and Signal Processing, 2019, 118:477-502. （SCI，中科院一区Top，IF：8.934，ESI高被引论文）
[6]Hua Li, Tao Liu, Xing Wu, Qing Chen. Application of EEMD and improved frequency band entropy in bearing fault feature extraction[J]. ISA Transactions, 2019, 88:170-185.（SCI，中科院二区Top，IF：5.911）
[7]Hua Li, Tao Liu, Xing Wu, Shaobo Li. Rotating Machinery Fault Diagnosis Based on Typical Resonance Demodulation Methods: A Review[J]. IEEE Sensors Journal, 2023, Early Access, doi: 10.1109/JSEN.2023.3235585.（SCI，中科院二区Top，IF：4.325）
[8]Hua Li, Tao Liu, Xing Wu, Qing Chen. An Optimized VMD Method and Its Applications in Bearing Fault Diagnosis[J]. Measurement, 2020:108185. （SCI，中科院二区，IF：5.131）
[9]Hua Li, Tao Liu, Xing Wu, Shaobo Li. Research on Test Bench Bearing Fault Diagnosis of Improved EEMD Based on Improved Adaptive Resonance Technology[J]. Measurement, 2021, 109986. （SCI，中科院二区，IF：5.131）
[10]Hua Li, Xing Wu, Tao Liu, Shaobo Li. Composite fault diagnosis for rolling bearing based on parameter-optimized VMD[J]. Measurement, 2022, 201:111637. （SCI，中科院二区，IF：5.131）
[11]李华, 刘韬, 伍星, 李少波. 相关奇异值比的SVD在轴承故障诊断中的应用[J]. 机械工程学报, 2021, 57(21): 138-149。（EI源刊，一级学报，卓越行动计划梯队期刊）
[12]李华, 伍星, 刘韬, 陈庆. 基于信息熵优化变分模态分解的滚动轴承故障特征提取[J]. 振动与冲击, 2018, 37(23): 219-225. （EI源刊，入选2021年领跑者5000-中国精品科技期刊顶尖学术论文）
[13]李华, 伍星, 刘韬, 陈庆. 变分模态分解和改进的自适应共振技术在轴承故障特征提取中的应用[J]. 振动工程学报, 2018, 31(04): 718-726. （EI源刊，一级学报）
[14]李华, 刘韬, 伍星, 陈庆. EEMD和优化的频带熵应用于轴承故障特征提取[J]. 振动工程学报, 2020, 33(2): 414-423. （EI源刊，一级学报）
