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Changqing Shen
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2020 – today
- 2024
- [j55]Zhenzhong He, Changqing Shen, Bojian Chen
, Juanjuan Shi, Weiguo Huang, Zhongkui Zhu, Dong Wang
A new feature boosting based continual learning method for bearing fault diagnosis with incremental fault types. Adv. Eng. Informatics 61: 102469 (2024) - [j54]Xiao Zhang, Weiguo Huang
Cross-Supervised multisource prototypical network: A novel domain adaptation method for multi-source few-shot fault diagnosis. Adv. Eng. Informatics 61: 102538 (2024) - [j53]Qitong Chen
Fault diagnosis for ball screws in industrial robots under variable and inaccessible working conditions with non-vibration signals. Adv. Eng. Informatics 62: 102617 (2024) - [j52]Yan Zhang
Adaptive feature consolidation residual network for exemplar-free continuous diagnosis of rotating machinery with fault-type increments. Adv. Eng. Informatics 62: 102715 (2024) - [j51]Mingkuan Shi, Chuancang Ding, Changqing Shen, Weiguo Huang, Zhongkui Zhu:
Imbalanced class incremental learning system: A task incremental diagnosis method for imbalanced industrial streaming data. Adv. Eng. Informatics 62: 102832 (2024) - [j50]Mingkuan Shi, Chuancang Ding
Semi-supervised class incremental broad network for continuous diagnosis of rotating machinery faults with limited labeled samples. Knowl. Based Syst. 286: 111397 (2024) - [j49]Yan Zhang
Deep adaptive sparse residual networks: A lifelong learning framework for rotating machinery fault diagnosis with domain increments. Knowl. Based Syst. 293: 111679 (2024) - [j48]Jun Wang
Multi-scale style generative and adversarial contrastive networks for single domain generalization fault diagnosis. Reliab. Eng. Syst. Saf. 243: 109879 (2024) - [j47]Hongyan Zhu, Changqing Shen
Reserving embedding space for new fault types: A new continual learning method for bearing fault diagnosis. Reliab. Eng. Syst. Saf. 252: 110433 (2024) - [j46]Mingkuan Shi
Cross-Domain Class Incremental Broad Network for Continuous Diagnosis of Rotating Machinery Faults Under Variable Operating Conditions. IEEE Trans. Ind. Informatics 20(4): 6356-6368 (2024) - [j45]Qitong Chen
Metric Learning-Based Few-Shot Adversarial Domain Adaptation: A Cross-Machine Diagnosis Method for Ball Screws of Industrial Robots. IEEE Trans. Instrum. Meas. 73: 1-10 (2024) - [j44]Weizhen Liu
Point Rail of High-Speed Railway Turnout Induced Feature Extraction Using Oscillatory Behavior-Based Signal Sparse Decomposition. IEEE Trans. Instrum. Meas. 73: 1-13 (2024) - [j43]Jun Zhu
A New Incremental Learning for Bearing Fault Diagnosis Under Noisy Conditions Using Classification and Feature-Level Information. IEEE Trans. Instrum. Meas. 73: 1-14 (2024) - 2023
- [j42]Hanting Zhou, Wenhe Chen, Changqing Shen, Longsheng Cheng
Intelligent machine fault diagnosis with effective denoising using EEMD-ICA- FuzzyEn and CNN. Int. J. Prod. Res. 61(23): 8252-8264 (2023) - [j41]Mingkuan Shi, Chuancang Ding, Rui Wang, Qiuyu Song, Changqing Shen, Weiguo Huang, Zhongkui Zhu:
Deep hypergraph autoencoder embedding: An efficient intelligent approach for rotating machinery fault diagnosis. Knowl. Based Syst. 260: 110172 (2023) - [j40]Rui Wang, Weiguo Huang, Xiao Zhang, Jun Wang, Chuancang Ding, Changqing Shen:
Federated contrastive prototype learning: An efficient collaborative fault diagnosis method with data privacy. Knowl. Based Syst. 281: 111093 (2023) - [j39]Qi Li
Cross-domain augmentation diagnosis: An adversarial domain-augmented generalization method for fault diagnosis under unseen working conditions. Reliab. Eng. Syst. Saf. 234: 109171 (2023) - [j38]Rui Wang
A novel domain generalization network with multidomain specific auxiliary classifiers for machinery fault diagnosis under unseen working conditions. Reliab. Eng. Syst. Saf. 238: 109463 (2023) - [j37]Mingkuan Shi, Chuancang Ding
Graph embedding deep broad learning system for data imbalance fault diagnosis of rotating machinery. Reliab. Eng. Syst. Saf. 240: 109601 (2023) - [j36]Shilong Sun
Editorial for Special Issue: Machine Health Monitoring and Fault Diagnosis Techniques. Sensors 23(7): 3493 (2023) - [j35]Zenghui An
Actively Imaginative Data Augmentation for Machinery Diagnosis Under Large-Speed-Fluctuation Conditions. IEEE Trans. Ind. Informatics 19(7): 8484-8495 (2023) - [j34]Yao Liu
A Lifelong Learning Method Based on Generative Feature Replay for Bearing Diagnosis With Incremental Fault Types. IEEE Trans. Instrum. Meas. 72: 1-11 (2023) - [j33]Linghui Lu
Dual Contrastive Learning for Semi-Supervised Fault Diagnosis Under Extremely Low Label Rate. IEEE Trans. Instrum. Meas. 72: 1-12 (2023) - [j32]Changqing Shen
A New Multisource Domain Bearing Fault Diagnosis Method With Adaptive Dual-Domain Obfuscation Weighting Strategy. IEEE Trans. Instrum. Meas. 72: 1-11 (2023) - [j31]Shilong Sun
A Data Privacy Protection Diagnosis Framework for Multiple Machines Vibration Signals Based on a Swarm Learning Algorithm. IEEE Trans. Instrum. Meas. 72: 1-9 (2023) - [j30]Rui Wang
Classifier Discrepancy Guided Soft-Weight Adaptation Network for Machinery Fault Diagnosis Under Domain and Category Shift. IEEE Trans. Instrum. Meas. 72: 1-10 (2023) - [i1]Changqing Shen, Sihao Mao, Bingzhou Xu, Ziwei Wang, Xiaojian Zhang, Sijie Yan, Han Ding:
Spiral Complete Coverage Path Planning Based on Conformal Slit Mapping in Multi-connected Domains. CoRR abs/2309.10655 (2023) - 2022
- [j29]Xuegang Li, Xingxing Jiang
Multi-perspective deep transfer learning model: A promising tool for bearing intelligent fault diagnosis under varying working conditions. Knowl. Based Syst. 243: 108443 (2022) - [j28]Rui Wang, Weiguo Huang
Federated adversarial domain generalization network: A novel machinery fault diagnosis method with data privacy. Knowl. Based Syst. 256: 109880 (2022) - [j27]Tengyi Peng
Fault Feature Extractor Based on Bootstrap Your Own Latent and Data Augmentation Algorithm for Unlabeled Vibration Signals. IEEE Trans. Ind. Electron. 69(9): 9547-9555 (2022) - [j26]Liang Chen
Adversarial Domain-Invariant Generalization: A Generic Domain-Regressive Framework for Bearing Fault Diagnosis Under Unseen Conditions. IEEE Trans. Ind. Informatics 18(3): 1790-1800 (2022) - [j25]Jun Zhu
Cross-Domain Open-Set Machinery Fault Diagnosis Based on Adversarial Network With Multiple Auxiliary Classifiers. IEEE Trans. Ind. Informatics 18(11): 8077-8086 (2022) - [j24]Bojian Chen
A Lifelong Learning Method for Gearbox Diagnosis With Incremental Fault Types. IEEE Trans. Instrum. Meas. 71: 1-10 (2022) - [j23]Jingde Li
A New Adversarial Domain Generalization Network Based on Class Boundary Feature Detection for Bearing Fault Diagnosis. IEEE Trans. Instrum. Meas. 71: 1-9 (2022) - [j22]Juanjuan Shi
Instantaneous Frequency Synchronized Generalized Stepwise Demodulation Transform for Bearing Fault Diagnosis. IEEE Trans. Instrum. Meas. 71: 1-15 (2022) - [j21]Rui Wang
Multisource Domain Feature Adaptation Network for Bearing Fault Diagnosis Under Time-Varying Working Conditions. IEEE Trans. Instrum. Meas. 71: 1-10 (2022) - [j20]Tongtong Yan
Integration of a Novel Knowledge-Guided Loss Function With an Architecturally Explainable Network for Machine Degradation Modeling. IEEE Trans. Instrum. Meas. 71: 1-12 (2022) - [c7]Bojian Chen
Lifelong Learning for Bearing Fault Diagnosis with Incremental Fault Types. ICPHM 2022: 114-120 - 2021
- [j19]Xin Li
Multi-sensor gearbox fault diagnosis by using feature-fusion covariance matrix and multi-Riemannian kernel ridge regression. Reliab. Eng. Syst. Saf. 216: 108018 (2021) - [j18]Jun Zhu
A New Multiple Source Domain Adaptation Fault Diagnosis Method Between Different Rotating Machines. IEEE Trans. Ind. Informatics 17(7): 4788-4797 (2021) - [j17]Yongxiang Li
Extended Noise Resistant Correlation Method for Period Estimation of Pseudoperiodic Signals. IEEE Trans. Instrum. Meas. 70: 1-11 (2021) - [j16]Yongxiang Li
Generalized Autocorrelation Method for Fault Detection Under Varying-Speed Working Conditions. IEEE Trans. Instrum. Meas. 70: 1-11 (2021) - [j15]Ruixian Li
Intelligent Bearing Fault Diagnosis Based on Scaled Ramanujan Filter Banks in Noisy Environments. IEEE Trans. Instrum. Meas. 70: 1-13 (2021) - [j14]Yi Liao
Enhanced Sparse Regularization Based on Logarithm Penalty and Its Application to Gearbox Compound Fault Diagnosis. IEEE Trans. Instrum. Meas. 70: 1-12 (2021) - [j13]Haidong Shao
Fault Diagnosis of a Rotor-Bearing System Under Variable Rotating Speeds Using Two-Stage Parameter Transfer and Infrared Thermal Images. IEEE Trans. Instrum. Meas. 70: 1-11 (2021) - [j12]Changqing Shen
Dynamic Joint Distribution Alignment Network for Bearing Fault Diagnosis Under Variable Working Conditions. IEEE Trans. Instrum. Meas. 70: 1-13 (2021) - 2020
- [j11]Wei You
An Intelligent Deep Feature Learning Method With Improved Activation Functions for Machine Fault Diagnosis. IEEE Access 8: 1975-1985 (2020) - [j10]Xu Wang, Changqing Shen
Multi-scale deep intra-class transfer learning for bearing fault diagnosis. Reliab. Eng. Syst. Saf. 202: 107050 (2020) - [c6]Qi Li, Shuangjie Liu, Bingru Yang, Yiyun Xu, Liang Chen, Changqing Shen
Adversarial multi-domain adaptation for machine fault diagnosis with variable working conditions. INDIN 2020: 737-741 - [c5]Jun Zhu
Multi-source Unsupervised Domain Adaptation for Machinery Fault Diagnosis under Different Working Conditions. INDIN 2020: 755-762
2010 – 2019
- 2019
- [j9]Juanjuan Shi
Dual-Guidance-Based Optimal Resonant Frequency Band Selection and Multiple Ridge Path Identification for Bearing Fault Diagnosis Under Time-Varying Speeds. IEEE Access 7: 144995-145012 (2019) - [j8]Yumei Qi, Changqing Shen
A New Deep Fusion Network for Automatic Mechanical Fault Feature Learning. IEEE Access 7: 152552-152563 (2019) - [j7]Tao Jiang, Jun Wang
Multi-Bandwidth Mode Manifold for Fault Diagnosis of Rolling Bearings. IEEE Access 7: 179620-179633 (2019) - [c4]Dong Wang
Discovery of a Simplified Index Commonly Used in Various Algorithms for Quantification of Repetitive Transients. AIM 2019: 863-867 - [c3]Yumei Qi, Changqing Shen
Adaptive Morphological Feature Extraction and Support Vector Regressive Classification for Gearbox Fault Diagnosis. AIM 2019: 868-872 - 2018
- [j6]Jiaqi Xie, Guifu Du
An End-to-End Model Based on Improved Adaptive Deep Belief Network and Its Application to Bearing Fault Diagnosis. IEEE Access 6: 63584-63596 (2018) - [j5]Changqing Shen
An automatic and robust features learning method for rotating machinery fault diagnosis based on contractive autoencoder. Eng. Appl. Artif. Intell. 76: 170-184 (2018) - [j4]Shenghao Tang, Changqing Shen
Adaptive deep feature learning network with Nesterov momentum and its application to rotating machinery fault diagnosis. Neurocomputing 305: 1-14 (2018) - 2017
- [j3]Yumei Qi
Stacked Sparse Autoencoder-Based Deep Network for Fault Diagnosis of Rotating Machinery. IEEE Access 5: 15066-15079 (2017) - [c2]Shenghao Tang, Wei You, Changqing Shen
A self-adaptive deep belief network with Nesterov momentum for the fault diagnosis of rolling element bearings. ICDLT 2017: 1-5 - 2016
- [c1]Chunyan Luo, Changqing Shen
Sparse representation of gearbox compound fault features by combining Majorization-Minimization algorithm and wavelet bases. I2MTC 2016: 1-5 - 2014
- [j2]Fang Liu
Wayside Bearing Fault Diagnosis Based on a Data-Driven Doppler Effect Eliminator and Transient Model Analysis. Sensors 14(5): 8096-8125 (2014) - 2013
- [j1]Changqing Shen
A Doppler Transient Model Based on the Laplace Wavelet and Spectrum Correlation Assessment for Locomotive Bearing Fault Diagnosis. Sensors 13(11): 15726-15746 (2013)
Coauthor Index
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last updated on 2024-10-07 21:16 CEST by the dblp team
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