汤宝平

期刊论文

1. 张仁亮，向柏青，汤宝平（2026）. 滑动轴承-齿轮非线性双转子系统拍振机理研究. 《振动与冲击》.
2. Mengjie Luo, Yi Wang, Tao Zhang, Longting Chen, Yi Qin, Baoping Tang (2026). TF-RefineNet: A deep time–frequency refinement network and its application to tacho-less order tracking. Mechanical Systems and Signal Processing.DOI
3. Xiangsheng Tan, Qikang Li, Baoping Tang, Peng Zhu, Zihao Li, Bing Li (2026). Digital twin-enabled boundary-corrected regularized subdomain adaptive network for gear fault diagnosis under class imbalance. Measurement Science and Technology.DOI
4. Zhen Ming, Baoping Tang, Lei Deng, Qikang Li, Zihao Li, Xi Zhang (2026). Digital twin-enhanced framework for rolling bearings fault diagnosis under imbalanced and open-set conditions. Mechanical Systems and Signal Processing.DOI
5. Peng Zhu, Lei Deng, Baoping Tang, Zihao Li, Xi Zhang (2026). Learnable wavelet packet kernel guided deep discriminative dynamic joint domain adaptation network for cross-machine fault diagnosis under strong noise. ISA Transactions.DOI
6. Hao Tan, Baoping Tang, Hao Fu, Chunhua Zhao (2026). Array-Multiplexed CNN Hardware Accelerator for End-Side Fault Diagnosis in Resource-Constrained Wireless Sensor Networks. IEEE Sensors Journal.DOI
7. Yanling Wu, Baoping Tang, Xiaolong Yang, Qingqing Tian (2026). Accuracy-constrained automatic transfer pruning for edge-side fault diagnosis of wind-turbine gearboxes. Measurement Science and Technology.DOI
8. Qichao Yang, Baoping Tang, Lei Deng, Xiaolong Zhang, Jinzhou Wu (2025). A hybrid dual-frequency-informed spider net for RUL prognosis with adaptive IDP detection and outlier correction. Reliability Engineering & System Safety, Vol. 253.DOI
9. 朱朋，邓蕾，汤宝平，张小龙，刘永刚（2025）. 数字孪生驱动小波注意力迁移网络的齿轮箱故障诊断方法. 《仪器仪表学报》.DOI
10. Kai Zhang, Bing Wang, Qing Zheng, Guofu Ding, Jia-Hao Ma, Baoping Tang (2025). A novel fault diagnosis of high-speed train axle box bearings with adaptive curriculum self-paced learning under noisy labels. Structural Health Monitoring.DOI
11. Xiao-Xia Yu, Zhen Ma, Tingyao Liu, Zhigang Zhang, Baoping Tang (2025). Multi-head memory large language model for predicting degradation trends of gearbox under non-stationary excitation. Measurement.DOI
12. Xiao-Xia Yu, Zhigang Zhang, Baoping Tang, Jinghua Ma (2025). Non-Temporal Neural Networks for Predicting Degradation Trends of Key Wind-Turbine Gearbox Components. Renewable Energy.DOI
13. Jiahao Xiong, Feng Li, Baoping Tang, Yongming Wang, Ling Luo, Yongchao Wang, Daqing Tian (2025). Adversarial autoencoding Crossformer model with transfer learning for remaining service life prediction of rolling bearings. Measurement Science and Technology.DOI
14. Zhen Ming, Baoping Tang, Lei Deng, Xiaolong Zhang, Zihao Li (2025). Physics-enhanced simulation-to-measurement translation for rolling bearing fault diagnosis under limited samples. Engineering Applications of Artificial Intelligence.DOI
15. Peng Yi Zhu, Baoping Tang, Lei Deng, Jing Wei, Zihao Li, Qikang Li (2025). Vibration mechanism driven discrete wavelet hybrid attention weighted transfer network for partial domain fault diagnosis of gearboxes under data scarcity. Engineering Applications of Artificial Intelligence.DOI
16. Peng Han, Baoping Tang, Chongyang Zhang, Peng Yi Zhu (2025). Feature Augmented Label-Distribution-Aware Margin Loss for Fault Diagnosis Under Class Imbalance.DOI
17. Linhan Gou, Qikang Li, Baoping Tang, Xiaolong Zhang, Zihao Li, Yonggang Liu (2025). Margin-guided parameter decoupling-consensus framework for federated domain generalization in machinery fault diagnosis. Knowledge-Based Systems.DOI
18. Guangyao Zhang, Yi Wang, Xueyi Li, Yi Qin, Baoping Tang (2025). Hypothetical order test enhanced fault diagnosis architecture for rotating machinery under variable speed conditions. Mechanical Systems and Signal Processing.DOI
19. Peng Yi Zhu, Baoping Tang, Lei Deng, Qikang Li, Zihao Li (2025). Discriminative feature learning using class-aware and selective transfer adversarial network for partial cross-domain fault diagnosis of gearboxes. Engineering Applications of Artificial Intelligence.DOI
20. Runyan Zhao, Baoping Tang, Xiaolong Zhang, Lei Deng (2025). Physics-informed cross layer temporal frequency transformer network for remaining useful life prediction of rolling bearings. Engineering Applications of Artificial Intelligence.DOI
21. Yiyi Huang, Baoping Tang, Qichao Yang, Zhen Ming (2025). Physics-informed causal learning network for fault diagnosis of rotating machinery under unseen operating conditions. Neurocomputing.DOI
22. Hao Fu, Lei Deng, Baoping Tang, Shuaiwen Cui, Yuguang Fu (2025). Neural Networks Micro Memory Control Strategy for Mechanical Faults Edge Recognition. IEEE Transactions on Industrial Informatics.DOI
23. Chunhua Zhao, Baoping Tang, Lei Deng (2025). Measurements–Residuals Collaboration Sparse Reconstruction Under Missing Measurements in Wireless Sensor Networks for Mechanical Vibration Monitoring. IEEE Internet of Things Journal.DOI
24. Guangyao Zhang, Yi Wang, Yi Qin, Baoping Tang (2025). Statistical distribution measures based on amplitude normalization for wind turbine generator bearing condition monitoring under variable speed conditions. Mechanical Systems and Signal Processing.DOI
25. Qingjie Li, Yi Wang, Lihua Meng, Yi Qin, Baoping Tang (2025). SDMC-Net: A Lightweight and Deployable Fault Diagnosis Network Using Self-Distillation and Multiscale-Depth Convolution. IEEE Transactions on Instrumentation and Measurement.DOI
26. Lihua Meng, Baoping Tang, Yunpeng Bao, Chao Zhang, Shaoping Wang, Rentong Chen (2025). Optimization and design of T-type sealing structure based on compression ratio. IET conference proceedings..DOI
27. Qichao Yang, Baoping Tang, Lei Deng, Zhen Ming (2024). A hybrid physics-corrected neural network for RUL prognosis under random missing data. Expert Systems With Applications, Vol. 256.DOI
28. Qikang Li, Baoping Tang, Lei Deng, Qichao Yang, Peng Zhu (2024). Adaptive centroid prototype-based domain adaptation for fault diagnosis of rotating machinery without source data. Reliability Engineering & System Safety, Vol. 251.DOI
29. Yi Wang, Jiakai Ding, Haoran Sun, Yi Qin, Baoping Tang (2024). Deep signal separation for adaptive estimation of instantaneous phase from vibration signals. Expert Systems With Applications, Vol. 246.DOI
30. Shilong Yang, Baoping Tang, Weiying Wang, Qichao Yang, Cheng Hu (2024). Physics-informed multi-state temporal frequency network for RUL prediction of rolling bearings. Reliability Engineering & System Safety, Vol. 242.DOI
31. 熊佳豪，李锋，汤宝平，汪永超，罗玲（2024）. 基于策略梯度Informer模型的滚动轴承剩余寿命预测. 《工程科学与技术》.
32. 付豪，邓蕾，汤宝平，李子昊，吴艳灵（2024）. 资源受限的机械振动WSN层次分解CNN边缘计算方法. 《仪器仪表学报》.DOI
33. 姜沛轩，李锋，汤宝平，汪永超（2024）. 变分资格迹元强化循环网络用于空间滚动轴承剩余寿命预测. 《计算机集成制造系统》.
34. 金鸿，汤宝平，赵春华，杜思玉（2024）. 上下梁磁吸斥力双稳态压电能量采集器. 《仪器仪表学报》.DOI
35. 余晓霞，汤宝平，魏静，张志刚（2024）. 大转数波动条件下机理约束图权重增强网络的航空发动机附件机匣故障诊断方法. 《机械工程学报》.
36. 吴宣勇，黄忠全，李琪康，汤宝平（2024）. 无源数据约束下多源域自适应的风电齿轮箱故障诊断方法. 《太阳能学报》.
37. 王义，丁嘉凯，孙浩然，秦毅，汤宝平（2024）. 基于深度信号分离的航空发动机可解释智能诊断方法. 《机械工程学报》.
38. 刘峰良，李锋，汤宝平，汪永超，田大庆（2024）. 基于类对比簇分配异构迁移学习的空间滚动轴承寿命阶段识别. 《工程科学与技术》.
39. 汤宝平，罗浩，赵春华，黄艺（2024）. 大负载高功率振动能量收集同步整流方法. 《振动、测试与诊断》.
40. 汤宝平（2024）. 大型旋转机组健康管理系统软件通用平台研究. 《振动、测试与诊断》.
41. Xu-Wei Lai, Kai Zhang, Qing Zheng, Ming-Hang Zhao, Guofu Ding, Baoping Tang, Zisheng Li (2024). DP2Net: A discontinuous physical property-constrained single-source domain generalization network for tool wear state recognition. Mechanical systems and signal processing.DOI
42. Xiao-Xia Yu, Zhigang Zhang, Baoping Tang, Ming-Hang Zhao, Zhaowei Xiang, Xue-Cheng Wang, Xiao-Hai Wang (2024). A method based on DWRNet and MGAU for RUL prediction of bearing with few samples. Journal of Vibration and Control.DOI
43. Peng Yi Zhu, Lei Deng, Baoping Tang, Qichao Yang, Qikang Li (2024). Digital twin-enabled entropy regularized wavelet attention domain adaptation network for gearboxes fault diagnosis without fault data. Advanced Engineering Informatics.DOI
44. Jiakai Ding, Yi Wang, Yi Qin, Baoping Tang (2024). RTFNN: A refined time–frequency neural network for interpretable intelligent diagnosis of aero-engine. Advanced Engineering Informatics.DOI
45. Zhen Ming, Baoping Tang, Lei Deng, Qichao Yang, Qikang Li (2024). Digital twin-assisted fault diagnosis framework for rolling bearings under imbalanced data. Applied Soft Computing.DOI
46. Zhen Ming, Baoping Tang, Lei Deng, Qikang Li (2024). Simulation data-driven adaptive frequency filtering focal network for rolling bearing fault diagnosis. Engineering Applications of Artificial Intelligence.DOI
47. Zuqiang Su, Xiaolong Zhang, Guoyin Wang, Sheng Lu, Song Feng, Baoping Tang (2024). OPN: Open-Set Semi-Supervised Learning for Intelligent Fault Diagnosis of Rotating Machinery. IEEE Sensors Journal.DOI
48. Qichao Yang, Baoping Tang, Lei Deng, Zihao Li (2024). Adaptive early initial degradation point detection and outlier correction for bearings. Computers in Industry.DOI
49. Chengyuan Chen, Yi Wang, Yi Qin, Baoping Tang (2024). Low-Priori Intervention Transfer Learning Network for Large-Span Fault Diagnosis. IEEE Sensors Journal.DOI
50. Jiakai Ding, Yi Wang, Yi Qin, Baoping Tang (2024). Multi-objective optimal deep deconvolution and its application to early fault signal enhancement of rotating machineries. Mechanical Systems and Signal Processing.DOI
51. Qichao Yang, Baoping Tang, Lei Deng, Peng Zhu, Zhen Ming (2024). WTFormer: RUL prediction method guided by trainable wavelet transform embedding and lagged penalty loss. Advanced Engineering Informatics.DOI
52. Jiakai Ding, Hang Lu, Yi Wang, Yi Qin, Baoping Tang, Xiaoqing Dong (2024). Adaptive angle-weighted cumulative sum for interpretable machine condition monitoring. Applied Acoustics.DOI
53. Xiaoxia Yu, Zhigang Zhang, Baoping Tang, Minghang Zhao (2024). A multi-head self-attention autoencoder network for fault detection of wind turbine gearboxes under random loads*. Measurement Science and Technology.DOI
54. Xiaoxia Yu, Zhigang Zhang, Baoping Tang, Minghang Zhao (2024). Meta-Adaptive Graph Convolutional Networks With Few Samples for the Fault Diagnosis of Rotating Machinery. IEEE Sensors Journal.DOI
55. Qichao Yang, Baoping Tang, Qikang Li, Peng Zhu, Shilong Yang (2024). Physical mechanism-corrected degradation trend prediction network under data missing. ISA Transactions.DOI
56. Maoqi Ran, Baoping Tang, Peng Fei Sun, Qikang Li, Tielin Shi (2024). A gradient aligned domain adversarial network for unsupervised intelligent fault diagnosis of gearboxes. ISA Transactions.DOI
57. Chunhua Zhao, Baoping Tang, Lei Deng, Yi Huang, Hao Tan (2024). Global probability distribution structure-sparsity filter pruning for edge fault diagnosis in resource constrained wireless sensor networks. Engineering Applications of Artificial Intelligence.DOI
58. Jiawen Ding, Lei Deng, Qikang Li, Xinyu Gu, Baoping Tang (2024). Joint condition monitoring framework of wind turbines based on multi-task learning with poor-quality data. ISA Transactions.DOI
59. Li‐Wei Li, Lei Deng, Baoping Tang, Fuqi Wang (2024). Bi-objective flexible job shop scheduling on machines considering condition-based maintenance activities. Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability.DOI
60. Jiakai Ding, Yi Wang, Yi Qin, Baoping Tang (2024). Adaptive Global Noise Suppression Deep Deconvolution for Weak Fault Signature Mining of Aero-Engine Accessory Casing. IEEE Transactions on Instrumentation and Measurement.DOI
61. Chunhua Zhao, Baoping Tang, Lei Deng (2024). Missing-Measurements-Tolerant Compressed Sensing in Wireless Sensor Networks for Mechanical Vibration Monitoring. IEEE Transactions on Instrumentation and Measurement.DOI
62. Guangyao Zhang, Yi Wang, Zehao Fan, Yi Qin, Baoping Tang (2024). Statistically Interpretable Health Indicator Based on Dynamic Interactions Decoupling for Gear Wear Assessment. IEEE Transactions on Instrumentation and Measurement.DOI
63. Hao Fu, Lei Deng, Baoping Tang, Keyu Zhu (2024). Fusion Interpolation Codec in Wireless Sensor Network for Mechanical Vibration Monitoring. IEEE Transactions on Instrumentation and Measurement.DOI
64. Qikang Li, Baoping Tang, Lei Deng, Peng Zhu (2023). Source-free domain adaptation framework for fault diagnosis of rotation machinery under data privacy. Reliability Engineering & System Safety, Vol. 238.DOI
65. 叶泉兵，汤宝平，黄艺，赵春华，汤恒行（2023）. 机械振动WSN比例补偿跨层同步采集触发方法. 《仪器仪表学报》.DOI
66. 李统一，李锋，汤宝平，汪永超（2023）. 模型无关元迁移学习用于空间滚动轴承寿命阶段识别. 《振动工程学报》.
67. 舒帅，汤宝平，黄艺，赵春华，付豪（2023）. 机械振动WSN大量数据自适应传输控制方法. 《振动与冲击》.
68. 朱柯宇，汤宝平，付豪，汤恒行，何灏（2023）. 机械振动WSNs子带峰值自适应量化融合编解码方法. 《仪器仪表学报》.DOI
69. 张光耀，王义，李晓蒙，汤宝平，秦毅（2023）. 基于自适应谐波分量提取的航空发动机附件传动系统变速故障诊断方法. 《仪器仪表学报》.DOI
70. 张世界，魏静，汤宝平，吉科峰（2023）. 基于变系数滑模控制器的风电机组振动主动控制研究. 《太阳能学报》.
71. Xiaoxia Yu, Tang Baoping, WANG Weiying, WU Xuanyong, Biao Li (2023). Repairing Deteriorated Data of Wind Turbines by Multi-head Attention Bi-directional Long Short Time Memory Networks under Complex Working Conditions. Journal of Mechanical Engineering.DOI
72. Guangyao Zhang, Yi Wang, Liang Guo, Yi Qin, Baoping Tang, Haidong Shao (2023). Slice-Oriented Signal Probability Distribution Measure for Wind Turbine Generator Bearing Condition Monitoring Under Variable Speed Conditions. IEEE Transactions on Industrial Informatics.DOI
73. Xiaomeng Li, Yi Wang, Guangyao Zhang, Baoping Tang, Yi Qin (2023). Correlation warping radius tracking for condition monitoring of rolling bearings under varying operating conditions. Mechanical Systems and Signal Processing.DOI
74. Hao Fu, Lei Deng, Baoping Tang, Peng Zhu, Yi Huang (2023). Multivibration Sensors Data Fusion Codec for Mechanical Digital Twin. IEEE Sensors Journal.DOI
75. Zehao Fan, Yi Wang, Lihua Meng, Guangyao Zhang, Yi Qin, Baoping Tang (2023). Unsupervised Anomaly Detection Method for Bearing Based on VAE-GAN and Time-Series Data Correlation Enhancement (June 2023). IEEE Sensors Journal.DOI
76. Yanling Wu, Baoping Tang, Lei Deng, Yizhe Shen (2023). Hardware-Resource-Constrained Neural Architecture Search for Edge-Side Fault Diagnosis of Wind-Turbine Gearboxes. IEEE Transactions on Industrial Electronics.DOI
77. Xiaomeng Li, Yi Wang, Xiang Wan, Baoping Tang, Yi Qin, Caibin Xu (2023). Physics-informed deep filtering of ultrasonic guided waves for incipient defect inspection of large-scale square tube structures. Journal of Sound and Vibration.DOI
78. Chengyuan Chen, Yi Wang, Hulin Ruan, Yi Qin, Baoping Tang (2023). A robust intelligent fault diagnosis method for rotating machinery under noisy labels. Measurement Science and Technology.DOI
79. Qichao Yang, Baoping Tang, Yizhe Shen, Qikang Li (2023). Self-Attention Parallel Fusion Network for Wind Turbine Gearboxes Fault Diagnosis. IEEE Sensors Journal.DOI
80. Qichao Yang, Baoping Tang, Shilong Yang, Yizhe Shen (2023). An integrated network architecture for data repair and degradation trend prediction. Mechanical Systems and Signal Processing.DOI
81. Liaoyuan Huan, Baoping Tang, Chunhua Zhao (2023). Global Composite Compression of Deep Neural Network in Wireless Sensor Networks for Edge Intelligent Fault Diagnosis. IEEE Sensors Journal.DOI
82. Feng Li, Peixuan Jiang, Ling Luo, Baoping Tang, Yongchao Wang (2023). Variational eligibility trace meta-reinforcement recurrent network for residual life prediction of space rolling bearings. Applied Soft Computing.DOI
83. Kai Zhang, Zhixuan Li, Qing Shan Zheng, Guofu Ding, Baoping Tang, Minghang Zhao (2023). Fault Diagnosis With Bidirectional Guided Convolutional Neural Networks Under Noisy Labels. IEEE Sensors Journal.DOI
84. Qichao Yang, Baoping Tang, Qikang Li, Xiaoli Liu, Lei Bao (2023). Dual-frequency enhanced attention network for aircraft engine remaining useful life prediction. ISA Transactions.DOI
85. Jiakai Ding, Yi Wang, Yi Qin, Baoping Tang (2023). Deep time–frequency learning for interpretable weak signal enhancement of rotating machineries. Engineering Applications of Artificial Intelligence.DOI
86. Guangyao Zhang, Yi Wang, Xiaomeng Li, Yi Qin, Baoping Tang (2023). Health indicator based on signal probability distribution measures for machinery condition monitoring. Mechanical Systems and Signal Processing.DOI
87. Jiakai Ding, Yi Wang, Guangyao Zhang, Dongming Xiao, Yi Qin, Baoping Tang (2023). Slope synchronous chirplet transform and its application to tacho-less order tracking of rotating machineries. Mechanical Systems and Signal Processing.DOI
88. Cheng Li, Yi Wang, Guangyao Zhang, Yi Qin, Baoping Tang (2023). An enhanced instantaneous angular speed estimation method by multi-harmonic time–frequency realignment for wind turbine gearbox fault diagnosis. Measurement Science and Technology.DOI
89. Yi Huang, Guobiao Hu, Chaoyang Zhao, Baoping Tang, Xiaojing Mu, Yaowen Yang (2023). An L-shaped and bending-torsion coupled beam for self-adaptive vibration energy harvesting. Journal of Physics D Applied Physics.DOI
90. Chaoqun Duan, Yiwei Jiang, Huayan Pu, Jun Ting Luo, Fuqiang Liu, Baoping Tang (2023). Health prediction of partially observable failing systems under varying environments. ISA Transactions.DOI
91. Xiaomeng Li, Yi Wang, Hulin Ruan, Baoping Tang, Yi Qin (2023). Deep Manifold Learning for Weak Signal Detection. IEEE Transactions on Instrumentation and Measurement.DOI
92. Yanling Wu, Baoping Tang, Lei Deng, Qikang Li (2022). Distillation-enhanced fast neural architecture search method for edge-side fault diagnosis of wind turbine gearboxes. Expert Systems With Applications, Vol. 208.DOI
93. 肖家丰，董绍江，汤宝平，潘雪娇，胡小林，赵兴新（2022）. 基于PEDCC性能退化指标及MCRNN的滚动轴承寿命状态识别方法. 《振动与冲击》.
94. 李锋，王腾，汤宝平，田大庆（2022）. 基于滚动轴承故障诊断的类间排斥松弛判别迁移学习. 《工程科学与技术》.
95. 黄艺，赵春华，汤宝平，付豪，邓蕾（2022）. 冗余策略下的机械振动WSN高效可靠传输方法. 《仪器仪表学报》.DOI
96. 胡建川，汤宝平，黄艺，舒帅（2022）. 基于卡尔曼滤波的机械振动WSNs时间抖动累积误差抑制方法. 《中国测试》.
97. Chunhua Zhao, Baoping Tang, Lei Deng, Yi Huang, Qikang Li (2022). Multilevel Adaptive Near-Lossless Compression in Edge Collaborative Wireless Sensor Networks for Mechanical Vibration Monitoring. IEEE Transactions on Industrial Electronics.DOI
98. Xieyi Chen, Yi Wang, Haoran Sun, Hulin Ruan, Yi Qin, Baoping Tang (2022). A generalized degradation tendency tracking strategy for gearbox remaining useful life prediction. Measurement.DOI
99. Chunhua Zhao, Baoping Tang, Yi Huang, Hao Fu (2022). Multilayer Joint Optimization of Packet Size and Adaptive Transmission Scheduling of Wireless Sensor Networks for Mechanical Vibration Monitoring. IEEE Internet of Things Journal.DOI
100. Xiaoli Liu, Baoping Tang, Qikang Li, Qichao Yang (2022). Twin prototype networks with noisy label self-correction for fault diagnosis of wind turbine gearboxes. Measurement Science and Technology.DOI
101. Chunhua Zhao, Baoping Tang, Yi Huang, Lei Deng (2022). Edge Collaborative Compressed Sensing in Wireless Sensor Networks for Mechanical Vibration Monitoring. IEEE Transactions on Industrial Informatics.DOI
102. Xiaoxia Yu, Baoping Tang, Lei Deng (2022). Fault diagnosis of rotating machinery based on graph weighted reinforcement networks under small samples and strong noise. Mechanical Systems and Signal Processing.DOI
103. Jinghua Ma, Honglei Li, Baoping Tang, Jingshu Wang, Zheng Zou, Mingde Zhang (2022). Rolling bearing fault diagnosis based on improved VMD-adaptive wavelet threshold joint noise reduction. Advances in Mechanical Engineering.DOI
104. Yi Huang, Chunhua Zhao, Baoping Tang, Yaowen Yang, Hao Fu (2022). Sparse Random Reconstruction of Data Loss With Low Redundancy in Wireless Sensor Networks for Mechanical Vibration Monitoring. IEEE Sensors Journal.DOI
105. Yizhe Shen, Baoping Tang, Biao Li, Qian Tan, Yanling Wu (2022). Remaining useful life prediction of rolling bearing based on multi-head attention embedded Bi-LSTM network. Measurement.DOI
106. Xiaomeng Li, Yi Wang, Baoping Tang, Yi Qin, Guangyao Zhang (2022). Canonical correlation analysis of dimension reduced degradation feature space for machinery condition monitoring. Mechanical Systems and Signal Processing.DOI
107. Qikang Li, Baoping Tang, Lei Deng, Peng Xiong, Minghang Zhao (2022). Cross-Attribute adaptation networks: Distilling transferable features from multiple sampling-frequency source domains for fault diagnosis of wind turbine gearboxes. Measurement.DOI
108. Haoran Sun, Yi Wang, Hulin Ruan, Yi Qin, Baoping Tang, Baojia Chen (2022). A weak prior embedding-based method for transfer fault diagnosis of rolling bearing. Measurement.DOI
109. Hao Fu, Lei Deng, Baoping Tang, Chunhua Zhao, Yi Huang (2022). Time–Space Dynamic Incentives Topology Equilibrium Control for Mechanical Vibration Wireless Sensor Networks. IEEE Transactions on Industrial Informatics.DOI
110. Biao Li, Baoping Tang, Lei Deng, Jing Wei (2022). Joint attention feature transfer network for gearbox fault diagnosis with imbalanced data. Mechanical Systems and Signal Processing.DOI
111. Yi Huang, Chunhua Zhao, Baoping Tang, Hao Fu (2022). Beacon Synchronization-Based Multi-Channel With Dynamic Time Slot Assignment Method of WSNs for Mechanical Vibration Monitoring. IEEE Sensors Journal.DOI
112. Guangyao Zhang, Yi Wang, Xiaomeng Li, Baoping Tang, Yi Qin (2022). Enhanced symplectic geometry mode decomposition and its application to rotating machinery fault diagnosis under variable speed conditions. Mechanical Systems and Signal Processing.DOI
113. Minghang Zhao, Xuyun Fu, Yongjian Zhang, Linghui Meng, Baoping Tang (2022). Highly imbalanced fault diagnosis of mechanical systems based on wavelet packet distortion and convolutional neural networks. Advanced Engineering Informatics.DOI
114. Guangyao Zhang, Yi Wang, Xiaomeng Li, Yi Qin, Baoping Tang (2022). Dynamic Evaluation of Degradation Space Variation for Machine Condition Monitoring. IEEE Transactions on Instrumentation and Measurement.DOI
115. Yin Xiaoxia, DENG Lei, Baoping Tang, Yi Xia, L Qikang (2022). Gear Degradation Trend Prediction by Meta-learning Gated Recurrent Unit Networks under Few Samples. Journal of Mechanical Engineering.DOI
116. WANG Teng, Liu Feng, Ling Luo, Baoping Tang (2022). Life State Recognition of Space Rolling Bearings Based on Dual Scale Flexible Prototype Transfer Network. Journal of Mechanical Engineering.DOI
117. Sheng Xiang, Yi Qin, Jun Luo, Huayan Pu, Baoping Tang (2021). Multicellular LSTM-based deep learning model for aero-engine remaining useful life prediction. Reliability Engineering & System Safety, Vol. 216.DOI
118. 张焱，何姝钡，王平，汤宝平（2021）. 无转速计下变工况滚动轴承故障特征量化表征提取. 《仪器仪表学报》.DOI
119. 黄荣舟，汤宝平，杨燕妮，邓蕾（2021）. 基于长短时记忆网络融合SCADA数据的风电齿轮箱状态监测. 《太阳能学报》.DOI
120. 余晓霞，汤宝平，魏静，邓蕾（2021）. 强背景噪声条件下自适应图卷积神经网络的航空发动机附件机匣故障诊断方法. 《仪器仪表学报》.DOI
121. 李红贤，韩延，吴敬涛，汤宝平（2021）. 基于ICA包络增强MEMD的滚动轴承故障诊断. 《航空动力学报》.DOI
122. 董绍江，裴雪武，吴文亮，汤宝平，赵兴新（2021）. 改进抗干扰CNN的变负载滚动轴承损伤程度识别. 《振动、测试与诊断》.DOI
123. 谭杰，汤宝平，卓伟伟，李雁龙（2021）. 某型航空主减速器试车台测控系统设计. 《航空维修与工程》.
124. 任建亭，汤宝平，雍彬，邓蕾，张楷（2021）. 基于深度变分自编码网络融合SCADA数据的风电齿轮箱故障预警. 《太阳能学报》.DOI
125. 章国稳，汤宝平，陈卓（2021）. 多参考最小二乘复频域法的数值问题分析及优化. 《振动工程学报》.DOI
126. 雍彬，陈进，张方红，汤宝平（2021）. 基于门控循环网络融合多源数据的风电齿轮箱状态预警方法. 《太阳能学报》.DOI
127. Xuewu Pei, Shaojiang Dong, Baoping Tang, Pan Xuejiao (2021). Bearing Running State Recognition Method Based on Feature-to-Noise Energy Ratio and Improved Deep Residual Shrinkage Network. IEEE/ASME Transactions on Mechatronics.DOI
128. Hulin Ruan, Yi Wang, Xiaomeng Li, Yi Qin, Baoping Tang (2021). An enhanced non-local weakly supervised fault diagnosis method for rotating machinery. Measurement.DOI
129. Shijie Zhang, Jing Wei, Ziyang Xu, Baoping Tang, Rui Niu (2021). Research on the influence of system parameters on the electromechanical dynamics of a large wind turbine drivetrain. Energy Reports.DOI
130. Hulin Ruan, Yi Wang, Yi Qin, Baoping Tang (2021). An Enhanced Intelligent Fault Diagnosis Method to Combat Label Noise. International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD).DOI
131. Guangyao Zhang, Yi Wang, Yi Qin, Baoping Tang (2021). An Improved Symplectic Geometry Mode Decomposition Method for Rolling Bearing Fault Diagnosis under Variable Speed Conditions. International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD).DOI
132. Honghai Huang, Baoping Tang, Jun Luo, Huayan Pu, Kai Zhang (2021). Residual Gated Dynamic Sparse Network for Gearbox Fault Diagnosis Using Multisensor Data. IEEE Transactions on Industrial Informatics.DOI
133. Kai Zhang, Baoping Tang, Lei Deng, Xiaoxia Yu, Jing Wei (2021). Fault source location of wind turbine based on heterogeneous nodes complex network. Engineering Applications of Artificial Intelligence.DOI
134. Xiaomeng Li, Yi Wang, Hulin Ruan, Dong Wang, Yi Qin, Baoping Tang (2021). Deep transient feature learning for weak vibration signal detection. Measurement.DOI
135. Kai Zhang, Baoping Tang, Lei Deng, Xiaoli Liu (2021). A hybrid attention improved ResNet based fault diagnosis method of wind turbines gearbox. Measurement.DOI
136. Kai Zhang, Baoping Tang, Lei Deng, Qian Tan, Haoshuai Yu (2021). A fault diagnosis method for wind turbines gearbox based on adaptive loss weighted meta-ResNet under noisy labels. Mechanical Systems and Signal Processing.DOI
137. Hao Fu, Baoping Tang, Yi Huang, Lei Deng (2021). Path Perception Synchronization Trigger Method for Dual Mode Multiplexing Mechanical Vibration Wireless Sensor Networks. IEEE Access.DOI
138. Feng Li, Yangyang Cheng, Baoping Tang, Xueming Zhou, Daqing Tian (2021). Multi-layer gated temporal convolution network for residual useful life prediction of rotating machinery. Mechanical Systems and Signal Processing.DOI
139. Xiaoxia Yu, Baoping Tang, Kai Zhang (2021). Fault Diagnosis of Wind Turbine Gearbox Using a Novel Method of Fast Deep Graph Convolutional Networks. IEEE Transactions on Instrumentation and Measurement.DOI
140. Biao Li, Baoping Tang, Lei Deng, Minghang Zhao (2021). Self-Attention ConvLSTM and Its Application in RUL Prediction of Rolling Bearings. IEEE Transactions on Instrumentation and Measurement.DOI
141. Hulin Ruan, Yi Wang, Xiaomeng Li, Qin Yi, Baoping Tang, Ping Wanga (2021). A Relation-based Semi-supervised Method for Gearbox Fault Diagnosis with Limited Labeled Samples. IEEE Transactions on Instrumentation and Measurement.DOI
142. Kai Zhang, Baoping Tang, Lei Deng, Xiaoxia Yu (2021). Fault Detection of Wind Turbines by Subspace Reconstruction-Based Robust Kernel Principal Component Analysis. IEEE Transactions on Instrumentation and Measurement.DOI
143. Shaojiang Dong, Xuewu Pei, Wenliang Wu, Baoping Tang, Zhao Xingxin (2021). Rolling Bearing Fault Diagnosis Method Based on Multilayer Noise Reduction Technology and Improved Convolutional Neural Network. Journal of Mechanical Engineering.DOI
144. Shaojiang Dong, Xuewu Pei, Baoping Tang, Tian Kewei, Peng Yi Zhu, LI Yang, Zhao Xingxin (2021). Recognition of Rolling Bearing Life Status Based on FNER Performance Degradation Indicator and IDRSN. Journal of Mechanical Engineering.DOI
145. Renxiang Chen, Wu Haonian, Xia Zhang, Baoping Tang, Hu Caiping and Qin Xiaolin, Cai Dongyin (2021). Compound Fault Diagnosis of Rotating Machinery under Different Conditions Based on Subspace Embedded Feature Distribution Alignment. Journal of Mechanical Engineering.DOI
146. 宋宇宙，汤宝平，颜丙生（2020）. 基于EWT和ICA联合降噪的轴承故障诊断方法. 《组合机床与自动化加工技术》.DOI
147. 李锋，陈勇，王家序，汤宝平（2020）. 基于强化学习单元匹配循环神经网络的滚动轴承状态趋势预测. 《计算机集成制造系统》.DOI
148. 周陈林，董绍江，李玲，汤宝平，贺坤，穆书锋，张潇汀（2020）. 滚动轴承多状态特征信息的改进型卷积神经网络故障诊断方法. 《振动工程学报》.DOI
149. 汤宝平，熊学嫣，赵明航，谭骞（2020）. 多共振分量融合CNN的行星齿轮箱故障诊断. 《振动、测试与诊断》.
150. 程阳洋，李锋，汤宝平，田大庆（2020）. 量子基因链编码双向神经网络用于旋转机械剩余使用寿命预测. 《仪器仪表学报》.DOI
151. 李锋，陈勇，汤宝平，王家序（2020）. 强化学习长短时记忆神经网络用于状态预测. 《振动、测试与诊断》.DOI
152. 舒云龙，汤宝平，黄艺（2020）. 自适应时槽分配的机械振动WSNs传输休眠时序调度方法. 《装备环境工程》.
153. 石捷，汤宝平，李俊，舒云龙，黄艺（2020）. 振动能量收集与管理系统低能耗冷启动方法研究. 《重庆理工大学学报(自然科学)》.
154. 汤宝平，赵春华，曾超，肖鑫（2020）. 基于FAHP的机械振动WSN均衡拓扑构建方法. 《振动、测试与诊断》.
155. Fafa Chen, Lili Liu, Baoping Tang, Baojia Chen, Wenrong Xiao, Fajun Zhang (2020). A novel fusion approach of deep convolution neural network with auto-encoder and its application in planetary gearbox fault diagnosis. Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability.DOI
156. Biao Li, Baoping Tang, Lei Deng, Xiaoxia Yu (2020). Multiscale dynamic fusion prototypical cluster network for fault diagnosis of planetary gearbox under few labeled samples. Computers in Industry.DOI
157. Shaojiang Dong, Kun He, Baoping Tang (2020). The fault diagnosis method of rolling bearing under variable working conditions based on deep transfer learning. Journal of the Brazilian Society of Mechanical Sciences and Engineering.DOI
158. Peng Xiong, Baoping Tang, Lei Deng, Minghang Zhao, Xiaoxia Yu (2020). Multi-block domain adaptation with central moment discrepancy for fault diagnosis. Measurement.DOI
159. Xin Chen, Xingchen Ma, Weiwei Ren, Lingxiao Gao, Shan Lu, Daqiao Tong, Fayang Wang, Yu Chen, Yi Huang, Hao He, Baoping Tang, Jiajia Zhang, Xiaoqing Zhang, Xiaojing Mu, Ya Feng Yang (2020). A Triboelectric Nanogenerator Exploiting the Bernoulli Effect for Scavenging Wind Energy. Cell Reports Physical Science.DOI
160. Feng Li, Tuojiang Tang, Baoping Tang, Qiyuan He (2020). Deep convolution domain-adversarial transfer learning for fault diagnosis of rolling bearings. Measurement.DOI
161. Fanming Meng, Huali Han, Zhifei Ma, Baoping Tang (2020). Effects of Aviation Lubrication on Tribological Performances of Graphene/MoS2 Composite Coating. Journal of Tribology.DOI
162. Fafa Chen, Mengteng Cheng, Baoping Tang, Baojia Chen, Wenrong Xiao (2020). Pattern recognition of a sensitive feature set based on the orthogonal neighborhood preserving embedding and adaboost_SVM algorithm for rolling bearing early fault diagnosis. Measurement Science and Technology.DOI
163. Yong Chen, Feng Li, Jiaxu Wang, Baoping Tang, Xueming Zhou (2020). Quantum recurrent encoder–decoder neural network for performance trend prediction of rotating machinery. Knowledge-Based Systems.DOI
164. Minghang Zhao, Shisheng Zhong, Xuyun Fu, Baoping Tang, Shaojiang Dong, MICHAEL G. PECHT (2020). Deep Residual Networks With Adaptively Parametric Rectifier Linear Units for Fault Diagnosis. IEEE Transactions on Industrial Electronics.DOI
165. Qikang Li, Baoping Tang, Lei Deng, Yanling Wu, Yi Wang (2020). Deep balanced domain adaptation neural networks for fault diagnosis of planetary gearboxes with limited labeled data. Measurement.DOI
166. Fafa Chen, Mengteng Cheng, Baoping Tang, Wenrong Xiao, Baojia Chen, Xiaotao Shi (2020). A novel optimized multi-kernel relevance vector machine with selected sensitive features and its application in early fault diagnosis for rolling bearings. Measurement.DOI
167. Yi Huang, Baoping Tang, Lei Deng, Chunhua Zhao (2020). Fuzzy Analytic Hierarchy Process-Based Balanced Topology Control of Wireless Sensor Networks for Machine Vibration Monitoring. IEEE Sensors Journal.DOI
168. 孔子迁，邓蕾，汤宝平，韩延（2019）. 基于时频融合和注意力机制的深度学习行星齿轮箱故障诊断方法. 《仪器仪表学报》.DOI
169. 董绍江，贺坤，汤宝平，张潇汀，王艳（2019）. 基于损伤缺陷激励的滚动轴承振动机理分析. 《组合机床与自动化加工技术》.DOI
170. 李锋，向往，陈勇，汤宝平，王家序（2019）. 基于双隐层量子线路循环单元神经网络的状态退化趋势预测. 《机械工程学报》.
171. 陈法法，杨蕴鹏，汤宝平，肖文荣，陈保家，张发军（2019）. 组合核RVM与EEMD信息熵的机械设备可靠度评估与预测. 《工程科学与技术》.
172. 颜丙生，聂士杰，朱红瑜，汤宝平，马晓录（2019）. 基于虚拟仪器的便携式振动测试系统开发. 《实验室研究与探索》.
173. 汤宝平，周沿江，肖鑫，邓蕾（2019）. 时钟同步调度的多跳机械振动WSN多信道传输法. 《振动、测试与诊断》.DOI
174. 汤宝平，赵春华，邓蕾，肖鑫，黄艺（2019）. 机械振动WSNs最小二乘发射功率自适应控制方法. 《振动、测试与诊断》.DOI
175. 李俊，汤宝平，舒云龙，肖鑫（2019）. 自供电无线振动传感器网络的双模组振动能量收集与管理方法. 《中国测试》.
176. Feng Li, Xiang Wang, Yong Hui Chen, Tang Baoping, WANG Jiaxu (2019). State Degradation Trend Prediction Based on Double Hidden Layer Quantum Circuit Recurrent Unit Neural Network. Journal of Mechanical Engineering.DOI
177. XIAO Xin, Tang Bao-ping, DENG Lei, Yi Huang (2019). Accumulated Synchronous Acquisition Error Control Method Based on Cross-layer Design for Mechanical Vibration Wireless Sensor Networks. Journal of Mechanical Engineering.DOI
178. Minghang Zhao, Baoping Tang, Lei Deng, MICHAEL G. PECHT (2019). Multiple wavelet regularized deep residual networks for fault diagnosis. Measurement.DOI
179. Chang Xu, Baoping Tang, Qian Tan, Lei Deng, Fanghong Zhang (2019). One-dimensional fully decoupled networks for fault diagnosis of planetary gearboxes. Mechanical Systems and Signal Processing.DOI
180. Yi Wang, Baoping Tang, Yi Qin, Tao Huang (2019). Rolling Bearing Fault Detection of Civil Aircraft Engine Based on Adaptive Estimation of Instantaneous Angular Speed. IEEE Transactions on Industrial Informatics.DOI
181. Fafa Chen, Yunpeng Yang, Baoping Tang, Baojia Chen, Wenrong Xiao, Xianyou Zhong (2019). Performance degradation prediction of mechanical equipment based on optimized multi-kernel relevant vector machine and fuzzy information granulation. Measurement.DOI
182. Minghang Zhao, Shisheng Zhong, Xuyun Fu, Baoping Tang, MICHAEL G. PECHT (2019). Deep Residual Shrinkage Networks for Fault Diagnosis. IEEE Transactions on Industrial Informatics.DOI
183. Qin Yi, Yongfang Mao, Baoping Tang, Yi Wang, Haizhou Chen (2019). M-band flexible wavelet transform and its application to the fault diagnosis of planetary gear transmission systems. Mechanical Systems and Signal Processing.DOI
184. Xin Xiao, Lei Deng, Baoping Tang, Yan Han (2019). On-chip order tracking method using wireless sensor networks based on hardware cross-layer design. Measurement.DOI
185. Yi Wang, Bingchang Hou, Baoping Tang, Yi Qin (2019). Adaptive tacho information estimation for surveillance of rotatory machine under nonstationary conditions. HAL (Le Centre pour la Communication Scientifique Directe).
186. Ziqian Kong, Baoping Tang, Lei Deng, W.Y. Liu, Yan Han (2019). Condition monitoring of wind turbines based on spatio-temporal fusion of SCADA data by convolutional neural networks and gated recurrent units. Renewable Energy.DOI
187. Kai Zhang, Baoping Tang, Qin Yi, Lei Deng (2019). Fault diagnosis of planetary gearbox using a novel semi-supervised method of multiple association layers networks. Mechanical Systems and Signal Processing.DOI
188. Li Feng, Yong Chen, Jiaxu Wang, Xueming Zhou, Baoping Tang (2019). A reinforcement learning unit matching recurrent neural network for the state trend prediction of rolling bearings. Measurement.DOI
189. Yi Qin, Jingqiang Zou, Baoping Tang, Yi Wang, Haizhou Chen (2019). Transient Feature Extraction by the Improved Orthogonal Matching Pursuit and K-SVD Algorithm With Adaptive Transient Dictionary. IEEE Transactions on Industrial Informatics.DOI
190. Guowen Zhang, Baoping Tang, Zhuo Chen (2019). Operational modal parameter identification based on PCA-CWT. Measurement.DOI
191. Bingchang Hou, Yi Wang, Baoping Tang, Yi Qin, Yang Chen, Yuhang Chen (2019). A tacholess order tracking method for wind turbine planetary gearbox fault detection. Measurement.DOI
192. Yan Han, Baoping Tang, Lei Deng (2019). An enhanced convolutional neural network with enlarged receptive fields for fault diagnosis of planetary gearboxes. Computers in Industry.DOI
193. Yi Wang, Baoping Tang, Lihua Meng, Bingchang Hou (2019). Adaptive Estimation of Instantaneous Angular Speed for Wind Turbine Planetary Gearbox Fault Detection. IEEE Access.DOI
194. 颜丙生，聂士杰，汤宝平，刘自然（2018）. 基于阶次分析和EWT的轴承故障诊断研究. 《组合机床与自动化加工技术》.
195. 陈仁祥，黄鑫，杨黎霞，汤宝平，余腾伟，周君（2018）. 基于卷积神经网络和离散小波变换的滚动轴承故障诊断. 《振动工程学报》.
196. 李锋，陈勇，向往，王家序，汤宝平（2018）. 基于量子加权长短时记忆神经网络的状态退化趋势预测. 《仪器仪表学报》.DOI
197. Yi Wang, Peter Wai-Tat Tse, Baoping Tang, Yi Qin, Lei Deng, Tao Huang, Guanghua Xu (2018). Order spectrogram visualization for rolling bearing fault detection under speed variation conditions. Mechanical Systems and Signal Processing.DOI
198. Minghang Zhao, Myeongsu Kang, Baoping Tang, MICHAEL G. PECHT (2018). Multiple Wavelet Coefficients Fusion in Deep Residual Networks for Fault Diagnosis. IEEE Transactions on Industrial Electronics.DOI
199. Feng Li, Xiang Wang, Jiaxu Wang, Xueming Zhou, Baoping Tang (2018). Quantum weighted long short-term memory neural network and its application in state degradation trend prediction of rotating machinery. Neural Networks.DOI
200. Xiang Wang, Feng Li, Jiaxu Wang, Baoping Tang (2018). Quantum weighted gated recurrent unit neural network and its application in performance degradation trend prediction of rotating machinery. Neurocomputing.DOI
201. Yi Wang, Peter Wai-Tat Tse, Baoping Tang, Yi Qin, Lei Deng, Tao Huang (2018). Kurtogram manifold learning and its application to rolling bearing weak signal detection. Measurement.DOI
202. Yan Han, Baoping Tang, Lei Deng (2018). Multi-level wavelet packet fusion in dynamic ensemble convolutional neural network for fault diagnosis. Measurement.DOI
203. Yue Yu Zhao, Qin Yi, Lei Guo, Baoping Tang (2018). Modeling and Experiment of a V‐Shaped Piezoelectric Energy Harvester. Shock and Vibration.DOI
204. 陈海周，王家序，汤宝平，李俊阳（2017）. 基于最小熵解卷积和Teager能量算子直升机滚动轴承复合故障诊断研究. 《振动与冲击》.
205. 陈仁祥，黄鑫，杨黎霞，汤宝平，陈思杨，杨星（2017）. 加噪样本扩展深度稀疏自编码神经网络的滚动轴承寿命阶段识别. 《振动工程学报》.
206. 董绍江，王军，徐向阳，罗天洪，孙世政，汤宝平（2017）. 基于多SVM误差加权的轴承剩余寿命预测. 《制造技术与机床》.
207. 李锋，汤宝平，王家序，林建辉（2017）. 基于图嵌入概率半监督判别分析的故障辨识. 《机械工程学报》.
208. 汤宝平，罗雷，邓蕾，韩延（2017）. 风电机组传动系统振动监测研究进展. 《振动、测试与诊断》.
209. Minghang Zhao, Myeongsu Kang, Baoping Tang, MICHAEL G. PECHT (2017). Deep Residual Networks With Dynamically Weighted Wavelet Coefficients for Fault Diagnosis of Planetary Gearboxes. IEEE Transactions on Industrial Electronics.DOI
210. Qinwu Gao, W.Y. Liu, Baoping Tang, Guangwei Li (2017). A novel wind turbine fault diagnosis method based on intergral extension load mean decomposition multiscale entropy and least squares support vector machine. Renewable Energy.DOI
211. Renxiang Chen, Siyang Chen, Miao He, David He, Baoping Tang (2017). Rolling bearing fault severity identification using deep sparse auto-encoder network with noise added sample expansion. Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability.DOI
212. Shaojiang Dong, Dihua Sun, Xiangyang Xu, Baoping Tang (2017). Removal of power line interference of space bearing vibration signal based on the morphological filter and blind source separation. IOP Conference Series Earth and Environmental Science.DOI
213. Zuqiang Su, Hong Xiao, Yi Zhang, Baoping Tang, Yonghua Jiang (2017). Machinery running state identification based on discriminant semi-supervised local tangent space alignment for feature fusion and extraction. Measurement Science and Technology.DOI
214. Xin Xiao, Baoping Tang, Lei Deng (2017). High accuracy synchronous acquisition algorithm of multi-hop sensor networks for machine vibration monitoring. Measurement.DOI
215. Haizhou Chen, Jiaxu Wang, Junyang Li, Baoping Tang (2017). A texture-based rolling bearing fault diagnosis scheme using adaptive optimal kernel time frequency representation and uniform local binary patterns. Measurement Science and Technology.DOI
216. Yi Qin, Yongfang Mao, Baoping Tang (2017). Multicomponent decomposition by wavelet modulus maxima and synchronous detection. Mechanical Systems and Signal Processing.DOI
217. Yan Zhang, Baoping Tang, Yan Han, Lei Deng (2017). Bearing performance degradation assessment based on time-frequency code features and SOM network. Measurement Science and Technology.DOI
218. 张焱，汤宝平，熊鹏（2016）. 多尺度变异粒子群优化MK-LSSVM的轴承寿命预测. 《仪器仪表学报》.DOI
219. 曾超，邓蕾，张又进，汤宝平（2016）. 机械振动无线传感器网络数据分块大小研究. 《仪器仪表学报》.DOI
220. 汤宝平，邓兵，邓蕾，颜丙生（2016）. 无线传感器网络多级融合的机械故障诊断方法. 《振动、测试与诊断》.
221. 李锋，汤宝平，杨荣松（2016）. 基于Laplacian双生最小二乘支持向量机的早期故障辨识. 2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI).
222. Shaojiang Dong, Jun Wang, Baoping Tang, Xiangyang Xu, Juan Liu (2016). Bearing faults recognition based on the local mode decomposition morphological spectrum and optimized support vector machine. International Conference on Ubiquitous Robots and Ambient Intelligence.DOI
223. Guangwu Zhou, Jiaxu Wang, Yanfeng Han, Bo Wei, Baoping Tang, Ping Zhong (2016). An Experimental Study on Film Pressure Circumferential Distribution of Water-Lubricated Rubber Bearings with Multiple Grooves. Tribology Transactions.DOI
224. Minghang Zhao, Baoping Tang, Qian Tan (2016). Bearing remaining useful life estimation based on time–frequency representation and supervised dimensionality reduction. Measurement.DOI
225. Yao Jinbao, Baoping Tang, Jie Zhao (2016). Improved discrete Fourier transform algorithm for harmonic analysis of rotor system. Measurement.DOI
226. Yan Zhang, Baoping Tang, Xin Xiao (2016). Time–frequency interpretation of multi-frequency signal from rotating machinery using an improved Hilbert–Huang transform. Measurement.DOI
227. Zhongliang Lv, Baoping Tang, Yi Zhou, Chuande Zhou (2016). A Novel Method for Mechanical Fault Diagnosis Based on Variational Mode Decomposition and Multikernel Support Vector Machine. Shock and Vibration.DOI
228. Yao Jinbao, Baoping Tang, Jie Zhao (2016). A Fault Feature Extraction Method for Rolling Bearing Based on Pulse Adaptive Time-Frequency Transform. Shock and Vibration.DOI
229. Haizhou Chen, Jiaxu Wang, Baoping Tang, Ke Xiao, Junyang Li (2016). An integrated approach to planetary gearbox fault diagnosis using deep belief networks. Measurement Science and Technology.DOI
230. Yi Qin, Qingliang Zhang, Yongfang Mao, Baoping Tang (2016). Vibration component separation by iteratively using stochastic resonance with different frequency-scale ratios. Measurement.DOI
231. 马婧华，汤宝平，韩延（2015）. 风电机组传动系统网络化状态监测与故障诊断系统设计. 《重庆大学学报》.
232. 黄庆卿，汤宝平，邓蕾，张又进（2015）. 机械振动无线传感网络数据分块无损压缩方法. 《仪器仪表学报》.
233. 苏祖强，汤宝平，赵明航，秦毅（2015）. 基于多故障流形的旋转机械故障诊断. 《振动工程学报》.
234. 李锋，王家序，汤宝平，邓成军（2015）. 有监督不相关局部Fisher判别分析故障诊断. 《振动工程学报》.
235. 马婧华，汤宝平，宋涛（2015）. 基于自适应本征维数估计流形学习的相空间重构降噪方法. 《振动与冲击》.
236. 张焱，汤宝平，刘自然，陈仁祥（2015）. 时频表示特征约简的旋转机械故障特征提取方法. 《振动工程学报》.
237. Yan Zhang, Baoping Tang, Ziran Liu, Rengxiang Chen (2015). An adaptive demodulation approach for bearing fault detection based on adaptive wavelet filtering and spectral subtraction. Measurement Science and Technology.DOI
238. Yi Qin, Yi Tao, Yongfang Mao, Baoping Tang (2015). Quantitative rotor damage detection based on piezoelectric impedance. Measurement Science and Technology.DOI
239. Yi Qin, Baoping Tang, Yongfang Mao (2015). Adaptive signal decomposition based on wavelet ridge and its application. Signal Processing.DOI
240. Minghang Zhao, Baoping Tang, Qian Tan (2015). Fault diagnosis of rolling element bearing based on S transform and gray level co-occurrence matrix. Measurement Science and Technology.DOI
241. Feng Li, Minking K. Chyu, Jiaxu Wang, Baoping Tang (2015). Life grade recognition of rotating machinery based on Supervised Orthogonal Linear Local Tangent Space Alignment and Optimal Supervised Fuzzy C-Means Clustering. Measurement.DOI
242. Feng Li, Jiaxu Wang, Minking K. Chyu, Baoping Tang (2015). Weak fault diagnosis of rotating machinery based on feature reduction with Supervised Orthogonal Local Fisher Discriminant Analysis. Neurocomputing.DOI
243. Qingqing Huang, Baoping Tang, Lei Deng, Jiaxu Wang (2015). A divide-and-compress lossless compression scheme for bearing vibration signals in wireless sensor networks. Measurement.DOI
244. Qingqing Huang, Baoping Tang, Lei Deng (2015). Development of high synchronous acquisition accuracy wireless sensor network for machine vibration monitoring. Measurement.DOI
245. W.Y. Liu, Baoping Tang, Jian Han, Xiangning Lu, Ningning Hu, Zizhao He (2015). The structure healthy condition monitoring and fault diagnosis methods in wind turbines: A review. Renewable and Sustainable Energy Reviews.DOI
246. Shaojiang Dong, Lili Chen, Baoping Tang, Xiangyang Xu, Zhengyuan Gao, Juan Liu (2015). Rotating Machine Fault Diagnosis Based on Optimal Morphological Filter and Local Tangent Space Alignment. Shock and Vibration.DOI
247. 汤宝平，马婧华（2014）. 多准则融合敏感特征选择和自适应邻域的流形学习故障诊断. 《仪器仪表学报》.DOI
248. 陈仁祥，汤宝平，罗天洪，董绍江（2014）. 地面模拟真空环境中背景干扰的EEMD滤除方法. 《振动与冲击》.
249. 黄庆卿，汤宝平，邓蕾，肖鑫（2014）. 无线传感器网络子带能量自适应数据压缩方法. 《仪器仪表学报》.DOI
250. 黄庆卿，汤宝平，邓蕾，刘自然（2014）. 机械振动无线传感器网络跨层同步采集方法. 《仪器仪表学报》.
251. 陈法法，汤宝平，马婧华，尹爱军（2014）. 基于遗传退火优化MSVM的齿轮箱故障诊断. 《振动、测试与诊断》.
252. 汤宝平，黄庆卿，邓蕾，刘自然（2014）. 机械设备状态监测无线传感器网络研究进展. 《振动、测试与诊断》.
253. 苏祖强，汤宝平，邓蕾，尹爱军（2014）. 有监督LLTSA特征约简旋转机械故障诊断. 《仪器仪表学报》.DOI
254. 陈仁祥，汤宝平，杨黎霞，周广武（2014）. 自适应参数优化EEMD机械故障特征提取方法. 《振动、测试与诊断》.
255. Shaojiang Dong, Dihua Sun, Baoping Tang, Zhengyuan Gao, Yingrui Wang, Wentao Yu, Ming Xia (2014). Bearing degradation state recognition based on kernel PCA and wavelet kernel SVM. Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science.DOI
256. Zuqiang Su, Baoping Tang, Lei Deng, Ziran Liu (2014). Fault diagnosis method using supervised extended local tangent space alignment for dimension reduction. Measurement.DOI
257. Yao Jinbao, Baoping Tang, Jie Min Zhao (2014). A study on the quick measuring method of linear dynamic range of receiver. Measurement.DOI
258. Yi Qin, Yi Tao, Ye He, Baoping Tang (2014). Adaptive bistable stochastic resonance and its application in mechanical fault feature extraction. Journal of Sound and Vibration.DOI
259. Feng Li, Jiaxu Wang, Baoping Tang, Daqing Tian (2014). Life grade recognition method based on supervised uncorrelated orthogonal locality preserving projection and K-nearest neighbor classifier. Neurocomputing.DOI
260. Shaojiang Dong, Shirong Yin, Baoping Tang, Lili Chen, Tianhong Luo (2014). Bearing Degradation Process Prediction Based on the Support Vector Machine and Markov Model. Shock and Vibration.DOI
261. Shaojiang Dong, Dihua Sun, Baoping Tang, Zhenyuan Gao, Wentao Yu, Ming Xia (2014). A Fault Diagnosis Method for Rotating Machinery Based on PCA and Morlet Kernel SVM. Mathematical Problems in Engineering.DOI
262. 陈法法，汤宝平，苏祖强（2013）. 基于等距映射与加权KNN的旋转机械故障诊断. 《仪器仪表学报》.
263. 李锋，汤宝平，宋涛，丁行武（2013）. 归一Laplacian矩阵有监督最优局部保持映射故障辨识. 《机械工程学报》.
264. 张焱，汤宝平，邓蕾（2013）. 基于谱聚类初始化非负矩阵分解的机械故障诊断. 《仪器仪表学报》.DOI
265. 洪刚，汤宝平（2013）. 基于嵌入式双服务器的机械振动监测系统的设计与实现. 《仪表技术与传感器》.
266. 张志刚，石晓辉，施全，汤宝平（2013）. 基于改进EMD和谱峭度法滚动轴承故障特征提取. 《振动、测试与诊断》.
267. 陈法法，汤宝平，苏祖强（2013）. 基于局部切空间排列与MSVM的齿轮箱故障诊断. 《振动与冲击》.
268. 宋涛，汤宝平，李锋（2013）. 基于流形学习和K-最近邻分类器的旋转机械故障诊断方法. 《振动与冲击》.
269. 洪刚，汤宝平，裴勇（2013）. 分布式无线传感器节点覆盖集近似算法研究. 《微电子学与计算机》.DOI
270. 汤宝平，戴功伟，陈仁祥（2013）. 基于零相位转频跟踪带通滤波的旋转机械Bode图. 《振动、测试与诊断》.
271. Zuqiang Su, Baoping Tang, Jinghua Ma, Lei Deng (2013). Fault diagnosis method based on incremental enhanced supervised locally linear embedding and adaptive nearest neighbor classifier. Measurement.DOI
272. Fafa Chen, Baoping Tang, Tao Song, Li Li (2013). Multi-fault diagnosis study on roller bearing based on multi-kernel support vector machine with chaotic particle swarm optimization. Measurement.DOI
273. Shaojiang Dong, Baoping Tang, Renxiang Chen (2013). Bearing running state recognition based on non-extensive wavelet feature scale entropy and support vector machine. Measurement.DOI
274. Baoping Tang, Tao Song, Feng Li, Lei Deng (2013). Fault diagnosis for a wind turbine transmission system based on manifold learning and Shannon wavelet support vector machine. Renewable Energy.DOI
275. Feng Li, Baoping Tang, Rongsong Yang (2013). Rotating machine fault diagnosis using dimension reduction with linear local tangent space alignment. Measurement.DOI
276. Yi Qin, Yongfang Mao, Baoping Tang (2013). Vibration signal component separation by iteratively using basis pursuit and its application in mechanical fault detection. Journal of Sound and Vibration.DOI
277. 汤宝平，董绍江，马靖华（2012）. 基于独立分量分析的EMD模态混叠消除方法研究. 《仪器仪表学报》.DOI
278. 陈法法，汤宝平，黄庆卿（2012）. 免疫遗传优化Elman神经网络的旋转机械故障诊断. 《重庆大学学报》.
279. 汤宝平，蒋永华，姚金宝（2012）. 基于重分配魏格纳时频谱和SVD的故障诊断. 《振动、测试与诊断》.
280. 章国稳，汤宝平，唐光武（2012）. 基于数据缩减的分频段小波模态参数快速识别. 《振动工程学报》.
281. 董绍江，汤宝平，陈法法（2012）. 粒子群优化的多尺度形态滤波器消噪方法. 《重庆大学学报》.
282. 洪刚，汤宝平，裴勇（2012）. 基于感应区域像素的无线传感器最小覆盖集近似算法. 《微电子学与计算机》.
283. 张国垒，汤宝平，戴功伟（2012）. 面向机械参量的通用数据采集仪的设计. 《中国测试》.
284. 邸永峰，汤宝平，蔡巍巍（2012）. 面向机械振动监测的无线传感器网络节点的设计. 《中国测试》.
285. 汤宝平，阮启东，裴勇（2012）. 无线传感器网络倍增超周期多信道MAC协议设计. 《重庆大学学报》.
286. 陈仁祥，汤宝平，吕中亮（2012）. EEMD滤波的转子轴心轨迹提纯方法. 《重庆大学学报》.
287. 汤宝平，章国稳，孟利波（2012）. 基于模态能量的随机子空间虚假模态剔除. 《华中科技大学学报(自然科学版)》.
288. 章国稳，汤宝平，潘飞（2012）. 特征系统实现算法的虚假模态剔除方法. 《重庆大学学报》.
289. 蒋永华，汤宝平，陈法法（2012）. 应用最优重分配小波尺度谱的小波脊线提取. 《振动、测试与诊断》.
290. 洪刚，汤宝平，裴勇（2012）. 基于最低能耗路径的分簇路由算法. 《计算机仿真》.
291. 陈仁祥，汤宝平，吕中亮（2012）. 基于相关系数的EEMD转子振动信号降噪方法. 《振动、测试与诊断》.
292. 董绍江，汤宝平，张焱（2012）. 基于最优匹配跟踪算法的单通道机械信号盲源分离. 《振动工程学报》.
293. Fafa Chen, Baoping Tang, Renxiang Chen (2012). A novel fault diagnosis model for gearbox based on wavelet support vector machine with immune genetic algorithm. Measurement.DOI
294. Shaojiang Dong, Baoping Tang, Yan Zhang (2012). A repeated single-channel mechanical signal blind separation method based on morphological filtering and singular value decomposition. Measurement.DOI
295. Guowen Zhang, Baoping Tang, Guangwu Tang (2012). An improved stochastic subspace identification for operational modal analysis. Measurement.DOI
296. Tang Baoping (2012). Fault feature extraction of rolling element bearing based on improved EMD and sliding kurtosis algorithm. Zhendong yu chongji.
297. Wenyi Liu, Baoping Tang (2011). A hybrid time-frequency method based on improved Morlet wavelet and auto terms window. Expert Systems With Applications, Vol. 38, No. 6.DOI
298. 李锋，汤宝平，董绍江（2011）. 基于正交邻域保持嵌入特征约简的故障诊断模型. 《仪器仪表学报》.
299. 陈法法，汤宝平，董绍江（2011）. 基于粒子群优化LS-WSVM的旋转机械故障诊断. 《仪器仪表学报》.
300. 毛永芳，秦毅，汤宝平（2011）. 过完备有理小波变换在轴承故障诊断中的应用. 《振动、测试与诊断》.
301. 汤宝平，何启源，孟利波，章国稳（2011）. 短样本条件下提高HHT识别模态参数精度的方法. 《振动、测试与诊断》.
302. 邓蕾，胡小林，李锋，汤宝平（2011）. 基于支持向量机的BS-EMD端点效应消除方法. 《振动、测试与诊断》.
303. 董绍江，汤宝平，宋涛（2011）. 改进投票策略的Morlet小波核支持向量机及应用. 《振动、测试与诊断》.
304. 刘文艺，汤宝平，蒋永华（2011）. 一种自适应小波消噪方法. 《振动、测试与诊断》.
305. Baoping Tang, Shaojiang Dong, Tao Song (2011). Method for eliminating mode mixing of empirical mode decomposition based on the revised blind source separation. Signal Processing.DOI
306. Yi Qin, Baoping Tang, Jiaxu Wang, Ke Xiao (2011). A new method for multicomponent signal decomposition based on self-adaptive filtering. Measurement.DOI
307. Yonghua Jiang, Baoping Tang, Yi Qin, Wenyi Liu (2011). Feature extraction method of wind turbine based on adaptive Morlet wavelet and SVD. Renewable Energy.DOI
308. Tang Baoping, Feng Li, Renxiang Chen (2011). Fault diagnosis based on Littlewood-Paley wavelet support vector machine. Zhendong yu chongji.
309. Tang Baoping (2011). Tacholess Vold-Kalman order tracking of rotating machinery. Zhendong yu chongji.
310. 蒋永华，汤宝平，刘文艺，董绍江（2010）. 基于参数优化Morlet小波变换的故障特征提取方法. 《仪器仪表学报》.DOI
311. 李锋，汤宝平，刘文艺（2010）. 遗传算法优化最小二乘支持向量机的故障诊断. 《重庆大学学报》.
312. 蒋永华，汤宝平，董绍江（2010）. 自适应Morlet小波降噪方法及在轴承故障特征提取中的应用. 《仪器仪表学报》.
313. 汤宝平，蒋永华，董绍江（2010）. 重分配小波尺度谱的时频分布优化方法研究. 《仪器仪表学报》.
314. 汤宝平，习建民，李锋（2010）. 基于Elman神经网络的旋转机械故障诊断. 《计算机集成制造系统》.
315. 汤宝平，刘文艺，蒋永华（2010）. 基于交叉验证法优化参数的Morlet小波消噪方法. 《重庆大学学报》.
316. Baoping Tang, Wenyi Liu, Tao Song (2010). Wind turbine fault diagnosis based on Morlet wavelet transformation and Wigner-Ville distribution. Renewable Energy.DOI
317. Yi Qin, Jiaxu Wang, Baoping Tang, Yongfang Mao (2010). Higher density wavelet frames with symmetric low-pass and band-pass filters. Signal Processing.DOI
318. Wenyi Liu, Baoping Tang, Yonghua Jiang (2010). Status and problems of wind turbine structural health monitoring techniques in China. Renewable Energy.DOI
319. 王小平，汤宝平（2009）. 用于复杂设备健康状态监测的WSN节点设计. 《微计算机信息》.
320. Yi Qin, Baoping Tang, Jiaxu Wang (2009). Higher-density dyadic wavelet transform and its application. Mechanical Systems and Signal Processing.DOI
321. Baoping Tang, Fusu Li, Wengu Liu (2009). Using ASTFT Spectrum to Suppress Cross Terms in WVD and its Application in Fault Diagnosis. Materials science forum.DOI
322. Tang Baoping (2009). Multicomponent Demodulation Based on Iterated Hilbert Transform and Its Application.
323. 汤宝平，赵洁，姚金宝（2008）. 远程操控现有虚拟仪器的通用网络引擎研究. 《仪器仪表学报》.DOI
324. 李震，汤宝平，秦晓峰（2008）. 基于工控机的机械传动试验台测控系统的设计. 《现代制造工程》.DOI
325. 程发斌，汤宝平，何启源（2008）. 基于构件的时频分析仪的研究. 《仪器仪表学报》.
326. 徐聪，汤宝平，姚金宝（2007）. 输油泵机组远程状态监测系统的设计与实现. 《重庆大学学报》.
327. 汤宝平，钟佑明，程发斌（2007）. 基于HHT的非平稳信号分析仪的研究. 《仪器仪表学报》.DOI
328. Baoping Tang, Zhuo Chen, Yuguo Wei, Xiaofeng Qin (2007). Bluetooth-based distributed measurement system. Journal of Physics Conference Series.DOI
329. Baoping Tang, Yuanchang Zhong, Qiu Jian-wei (2006). Design of Onboard Instrument Based on Virtual Instrument Technology. Journal of Wuhan University of Technology-Mater Sci Ed.
330. Fabin Cheng, Baoping Tang, Qiyuan He (2006). Research on instantaneous feature of non-stationary signal based on hilbert-huang transform and wavelet packet decomposition.DOI
331. Tang Baoping (2006). VISUALIZATION OF THREE-DIMENSIONAL DATA FIELD AND ITS APPLICATION IN MACHINE TESTING. 《中国机械工程学报：英文版》.
332. 周传德，尹爱军，汤宝平（2005）. 秦氏模型智能控件化虚拟仪器系统及其本质特征. 《测控技术》.
333. 周传德，汤宝平（2005）. 基于秦氏模型的智能虚拟显示器的研究. 《仪器仪表学报》.DOI
334. Baoping Tang, Fabin Cheng, Aijun Yin (2005). Research on Virtual Instrument for Wavelet Transform.DOI
335. Baoping Tang, Fabin Cheng, Shuren Qin (2005). Study on virtual instrument developing system based on intelligent virtual control. Journal of Physics Conference Series.DOI
336. Tang Baoping (2005). IVC-Based Virtual Instrument Environment and its Feature. Measurement & Control Technology.
337. Tang Baoping (2004). Study on the marginal spectrum in Hilbert-Huang transform. Systems engineering and electronics.
338. 郭瑜，秦树人，汤宝平，纪跃波（2003）. 基于瞬时频率估计的旋转机械阶比跟踪. 《机械工程学报》.
339. 尹爱军，汤宝平，钟佑明（2003）. 虚拟测试仪器中三维空间数据场的实现. 《计量学报》.
340. 钟佑明，秦树人，汤宝平（2002）. Hilbert-Huang变换中的理论研究. 《振动与冲击》.
341. Shuren Qin, Rongxi Wei, Yu Guo, Baoping Tang (2002). The order tracking of rotating machinery based on instantaneous frequency estimation. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.DOI
342. Baoping Tang, Yuebo Ji, Chenggui Zhang, Shuren Qin (2002). Research on time-frequency analyzing theory and system. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE.DOI
343. 钟佑明，秦树人，汤宝平（2001）. 关于DFT中的延拓原理及计算结果物理意义的一些讨论. 《振动与冲击》.
344. 汤宝平，郑朝云，李碧蓉，文代刚（1999）. 输油泵机组状态监测分析诊断系统的设计. 《重庆交通大学学报(自然科学版)》.
345. 汤宝平，何玮，秦树人（1998）. Windows 环境下信号分析系统的设计. 《机械》.

预印本

1. Renxiang Chen, Yu Huang, Lixia Yang, Baoping Tang, Jialin Li (2025). A Digital Twin Model of Life-Cycle Rolling Bearing that Connects Measured and Virtual Signals by Goa. SSRN Electronic Journal.DOI
2. Feng Lv, Yi Wang, Yi Qin, Baoping Tang (2022). A Weighted Multi-Scale L1/L2 Deconvolution Method and its Application for Bearing Fault Diagnosis. SSRN Electronic Journal.DOI
3. Feng Li, Yangyang Cheng, Baoping Tang, Xue‐Ming Zhou, Xiong Rui-ping (2020). Quantum Gene Chain Coding Bidirectional Neural Network for Residual Useful Life Prediction of Rotating Machinery. Research Square.DOI