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Baoping Tang
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2020 – today
- 2024
- [j47]Qichao Yang, Baoping Tang
, Lei Deng, Peng Zhu, Zhen Ming:
WTFormer: RUL prediction method guided by trainable wavelet transform embedding and lagged penalty loss. Adv. Eng. Informatics 62: 102710 (2024) - [j46]Chunhua Zhao
, Baoping Tang, Lei Deng, Yi Huang, Hao Tan:
Global probability distribution structure-sparsity filter pruning for edge fault diagnosis in resource constrained wireless sensor networks. Eng. Appl. Artif. Intell. 133: 108319 (2024) - [j45]Yi Wang
, Jiakai Ding
, Haoran Sun, Yi Qin, Baoping Tang:
Deep signal separation for adaptive estimation of instantaneous phase from vibration signals. Expert Syst. Appl. 246: 123187 (2024) - [j44]Shilong Yang, Baoping Tang
, Weiying Wang, Qichao Yang
, Cheng Hu:
Physics-informed multi-state temporal frequency network for RUL prediction of rolling bearings. Reliab. Eng. Syst. Saf. 242: 109716 (2024) - [j43]Qikang Li, Baoping Tang, Lei Deng, Qichao Yang, Peng Zhu:
Adaptive centroid prototype-based domain adaptation for fault diagnosis of rotating machinery without source data. Reliab. Eng. Syst. Saf. 251: 110393 (2024) - [j42]Yanling Wu
, Baoping Tang
, Lei Deng
, Yizhe Shen
:
Hardware-Resource-Constrained Neural Architecture Search for Edge-Side Fault Diagnosis of Wind-Turbine Gearboxes. IEEE Trans. Ind. Electron. 71(8): 9812-9822 (2024) - [j41]Guangyao Zhang
, Yi Wang
, Liang Guo
, Yi Qin
, Baoping Tang
, Haidong Shao
:
Slice-Oriented Signal Probability Distribution Measure for Wind Turbine Generator Bearing Condition Monitoring Under Variable Speed Conditions. IEEE Trans. Ind. Informatics 20(4): 5297-5307 (2024) - [j40]Jiakai Ding
, Yi Wang
, Yi Qin
, Baoping Tang
:
Adaptive Global Noise Suppression Deep Deconvolution for Weak Fault Signature Mining of Aero-Engine Accessory Casing. IEEE Trans. Instrum. Meas. 73: 1-13 (2024) - [j39]Guangyao Zhang
, Yi Wang
, Zehao Fan
, Yi Qin
, Baoping Tang
:
Statistically Interpretable Health Indicator Based on Dynamic Interactions Decoupling for Gear Wear Assessment. IEEE Trans. Instrum. Meas. 73: 1-12 (2024) - [j38]Chunhua Zhao
, Baoping Tang
, Lei Deng
:
Missing-Measurements-Tolerant Compressed Sensing in Wireless Sensor Networks for Mechanical Vibration Monitoring. IEEE Trans. Instrum. Meas. 73: 1-13 (2024) - 2023
- [j37]Feng Li, Peixuan Jiang, Ling Luo, Baoping Tang, Yongchao Wang:
Variational eligibility trace meta-reinforcement recurrent network for residual life prediction of space rolling bearings. Appl. Soft Comput. 145: 110582 (2023) - [j36]Jiakai Ding
, Yi Wang, Yi Qin, Baoping Tang:
Deep time-frequency learning for interpretable weak signal enhancement of rotating machineries. Eng. Appl. Artif. Intell. 124: 106598 (2023) - [j35]Chunhua Zhao
, Baoping Tang
, Yi Huang
, Hao Fu
:
Multilayer Joint Optimization of Packet Size and Adaptive Transmission Scheduling of Wireless Sensor Networks for Mechanical Vibration Monitoring. IEEE Internet Things J. 10(7): 6444-6455 (2023) - [j34]Qikang Li, Baoping Tang, Lei Deng, Peng Zhu:
Source-free domain adaptation framework for fault diagnosis of rotation machinery under data privacy. Reliab. Eng. Syst. Saf. 238: 109468 (2023) - [j33]Chunhua Zhao
, Baoping Tang
, Lei Deng
, Yi Huang
, Qikang Li
:
Multilevel Adaptive Near-Lossless Compression in Edge Collaborative Wireless Sensor Networks for Mechanical Vibration Monitoring. IEEE Trans. Ind. Electron. 70(11): 11703-11713 (2023) - [j32]Hao Fu
, Lei Deng
, Baoping Tang
, Chunhua Zhao
, Yi Huang
:
Time-Space Dynamic Incentives Topology Equilibrium Control for Mechanical Vibration Wireless Sensor Networks. IEEE Trans. Ind. Informatics 19(5): 6305-6316 (2023) - [j31]Chunhua Zhao
, Baoping Tang
, Yi Huang
, Lei Deng
:
Edge Collaborative Compressed Sensing in Wireless Sensor Networks for Mechanical Vibration Monitoring. IEEE Trans. Ind. Informatics 19(8): 8852-8864 (2023) - [j30]Xiaomeng Li
, Yi Wang
, Hulin Ruan
, Baoping Tang
, Yi Qin
:
Deep Manifold Learning for Weak Signal Detection. IEEE Trans. Instrum. Meas. 72: 1-10 (2023) - 2022
- [j29]Minghang Zhao
, Xuyun Fu, Yongjian Zhang, Linghui Meng, Baoping Tang:
Highly imbalanced fault diagnosis of mechanical systems based on wavelet packet distortion and convolutional neural networks. Adv. Eng. Informatics 51: 101535 (2022) - [j28]Yanling Wu, Baoping Tang, Lei Deng, Qikang Li:
Distillation-enhanced fast neural architecture search method for edge-side fault diagnosis of wind turbine gearboxes. Expert Syst. Appl. 208: 118049 (2022) - [j27]Honghai Huang
, Baoping Tang
, Jun Luo
, Huayan Pu
, Kai Zhang
:
Residual Gated Dynamic Sparse Network for Gearbox Fault Diagnosis Using Multisensor Data. IEEE Trans. Ind. Informatics 18(4): 2264-2273 (2022) - [j26]Guangyao Zhang
, Yi Wang
, Xiaomeng Li
, Yi Qin
, Baoping Tang
:
Dynamic Evaluation of Degradation Space Variation for Machine Condition Monitoring. IEEE Trans. Instrum. Meas. 71: 1-10 (2022) - 2021
- [j25]Kai Zhang
, Baoping Tang
, Lei Deng, Xiaoxia Yu, Jing Wei:
Fault source location of wind turbine based on heterogeneous nodes complex network. Eng. Appl. Artif. Intell. 103: 104300 (2021) - [j24]Sheng Xiang, Yi Qin, Jun Luo, Huayan Pu, Baoping Tang:
Multicellular LSTM-based deep learning model for aero-engine remaining useful life prediction. Reliab. Eng. Syst. Saf. 216: 107927 (2021) - [j23]Minghang Zhao
, Shisheng Zhong, Xuyun Fu
, Baoping Tang
, Shaojiang Dong, Michael G. Pecht
:
Deep Residual Networks With Adaptively Parametric Rectifier Linear Units for Fault Diagnosis. IEEE Trans. Ind. Electron. 68(3): 2587-2597 (2021) - [j22]Biao Li
, Baoping Tang
, Lei Deng
, Minghang Zhao
:
Self-Attention ConvLSTM and Its Application in RUL Prediction of Rolling Bearings. IEEE Trans. Instrum. Meas. 70: 1-11 (2021) - [j21]Hulin Ruan, Yi Wang
, Xiaomeng Li, Yi Qin
, Baoping Tang
, Ping Wang
:
A Relation-Based Semisupervised Method for Gearbox Fault Diagnosis With Limited Labeled Samples. IEEE Trans. Instrum. Meas. 70: 1-13 (2021) - [j20]Xiaoxia Yu
, Baoping Tang
, Kai Zhang
:
Fault Diagnosis of Wind Turbine Gearbox Using a Novel Method of Fast Deep Graph Convolutional Networks. IEEE Trans. Instrum. Meas. 70: 1-14 (2021) - [j19]Kai Zhang
, Baoping Tang
, Lei Deng
, Xiaoxia Yu
:
Fault Detection of Wind Turbines by Subspace Reconstruction-Based Robust Kernel Principal Component Analysis. IEEE Trans. Instrum. Meas. 70: 1-11 (2021) - 2020
- [j18]Biao Li
, Baoping Tang, Lei Deng, Xiaoxia Yu:
Multiscale dynamic fusion prototypical cluster network for fault diagnosis of planetary gearbox under few labeled samples. Comput. Ind. 123: 103331 (2020) - [j17]Yong Chen, Feng Li, Jiaxu Wang, Baoping Tang, Xueming Zhou:
Quantum recurrent encoder-decoder neural network for performance trend prediction of rotating machinery. Knowl. Based Syst. 197: 105863 (2020) - [j16]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 Trans. Ind. Informatics 16(1): 215-227 (2020) - [j15]Minghang Zhao
, Shisheng Zhong, Xuyun Fu
, Baoping Tang
, Michael G. Pecht
:
Deep Residual Shrinkage Networks for Fault Diagnosis. IEEE Trans. Ind. Informatics 16(7): 4681-4690 (2020) - [j14]Yi Wang
, Baoping Tang
, Yi Qin
, Tao Huang
:
Rolling Bearing Fault Detection of Civil Aircraft Engine Based on Adaptive Estimation of Instantaneous Angular Speed. IEEE Trans. Ind. Informatics 16(7): 4938-4948 (2020)
2010 – 2019
- 2019
- [j13]Yi Wang
, Baoping Tang, Lihua Meng, Bingchang Hou
:
Adaptive Estimation of Instantaneous Angular Speed for Wind Turbine Planetary Gearbox Fault Detection. IEEE Access 7: 49974-49984 (2019) - [j12]Yan Han, Baoping Tang, Lei Deng:
An enhanced convolutional neural network with enlarged receptive fields for fault diagnosis of planetary gearboxes. Comput. Ind. 107: 50-58 (2019) - [j11]Minghang Zhao
, Myeongsu Kang
, Baoping Tang, Michael G. Pecht
:
Multiple Wavelet Coefficients Fusion in Deep Residual Networks for Fault Diagnosis. IEEE Trans. Ind. Electron. 66(6): 4696-4706 (2019) - 2018
- [j10]Wang Xiang, Feng Li, Jiaxu Wang, Baoping Tang:
Quantum weighted gated recurrent unit neural network and its application in performance degradation trend prediction of rotating machinery. Neurocomputing 313: 85-95 (2018) - [j9]Feng Li, Wang Xiang, Jiaxu Wang, Xueming Zhou, Baoping Tang:
Quantum weighted long short-term memory neural network and its application in state degradation trend prediction of rotating machinery. Neural Networks 106: 237-248 (2018) - [j8]Minghang Zhao
, Myeongsu Kang, Baoping Tang, Michael G. Pecht:
Deep Residual Networks With Dynamically Weighted Wavelet Coefficients for Fault Diagnosis of Planetary Gearboxes. IEEE Trans. Ind. Electron. 65(5): 4290-4300 (2018) - 2016
- [j7]Yi Qin, Baoping Tang, Yongfang Mao:
Adaptive signal decomposition based on wavelet ridge and its application. Signal Process. 120: 480-494 (2016) - [c2]Bingsheng Yan, Baoping Tang:
Simulation and testing of a non-linear ultrasonic system for testing the debonding of the adhesive layers of magnesium alloys. URAI 2016: 26-30 - [c1]Shaojiang Dong, Jun Wang, Baoping Tang, Xiangyang Xu
, Juan Liu:
Bearing faults recognition based on the local mode decomposition morphological spectrum and optimized support vector machine. URAI 2016: 1012-1016 - 2015
- [j6]Zuqiang Su, Baoping Tang, Ziran Liu, Yi Qin:
Multi-fault diagnosis for rotating machinery based on orthogonal supervised linear local tangent space alignment and least square support vector machine. Neurocomputing 157: 208-222 (2015) - [j5]Feng Li, Jiaxu Wang, Minking K. Chyu
, Baoping Tang:
Weak fault diagnosis of rotating machinery based on feature reduction with Supervised Orthogonal Local Fisher Discriminant Analysis. Neurocomputing 168: 505-519 (2015) - 2014
- [j4]Feng Li, Jiaxu Wang, Baoping Tang, Daqing Tian:
Life grade recognition method based on supervised uncorrelated orthogonal locality preserving projection and K-nearest neighbor classifier. Neurocomputing 138: 271-282 (2014) - 2012
- [j3]Baoping Tang, Shaojiang Dong, Tao Song:
Method for eliminating mode mixing of empirical mode decomposition based on the revised blind source separation. Signal Process. 92(1): 248-258 (2012) - 2011
- [j2]Wenyi Liu, Baoping Tang:
A hybrid time-frequency method based on improved Morlet wavelet and auto terms window. Expert Syst. Appl. 38(6): 7575-7581 (2011) - 2010
- [j1]Yi Qin, Jiaxu Wang, Baoping Tang, Yongfang Mao:
Higher density wavelet frames with symmetric low-pass and band-pass filters. Signal Process. 90(12): 3219-3231 (2010)
Coauthor Index
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last updated on 2024-08-15 23:46 CEST by the dblp team
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