Changqing Shen
Orcid: 0000-0002-5143-8366
According to our database1,
Changqing Shen
authored at least 63 papers
between 2013 and 2024.
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Bibliography
2024
Cross-Domain Class Incremental Broad Network for Continuous Diagnosis of Rotating Machinery Faults Under Variable Operating Conditions.
IEEE Trans. Ind. Informatics, April, 2024
Multi-scale style generative and adversarial contrastive networks for single domain generalization fault diagnosis.
Reliab. Eng. Syst. Saf., March, 2024
A New Incremental Learning for Bearing Fault Diagnosis Under Noisy Conditions Using Classification and Feature-Level Information.
IEEE Trans. Instrum. Meas., 2024
Point Rail of High-Speed Railway Turnout Induced Feature Extraction Using Oscillatory Behavior-Based Signal Sparse Decomposition.
IEEE Trans. Instrum. Meas., 2024
Metric Learning-Based Few-Shot Adversarial Domain Adaptation: A Cross-Machine Diagnosis Method for Ball Screws of Industrial Robots.
IEEE Trans. Instrum. Meas., 2024
Reserving embedding space for new fault types: A new continual learning method for bearing fault diagnosis.
Reliab. Eng. Syst. Saf., 2024
Deep adaptive sparse residual networks: A lifelong learning framework for rotating machinery fault diagnosis with domain increments.
Knowl. Based Syst., 2024
Semi-supervised class incremental broad network for continuous diagnosis of rotating machinery faults with limited labeled samples.
Knowl. Based Syst., 2024
Adaptive feature consolidation residual network for exemplar-free continuous diagnosis of rotating machinery with fault-type increments.
Adv. Eng. Informatics, 2024
Cross-Supervised multisource prototypical network: A novel domain adaptation method for multi-source few-shot fault diagnosis.
Adv. Eng. Informatics, 2024
Imbalanced class incremental learning system: A task incremental diagnosis method for imbalanced industrial streaming data.
Adv. Eng. Informatics, 2024
A new feature boosting based continual learning method for bearing fault diagnosis with incremental fault types.
Adv. Eng. Informatics, 2024
Fault diagnosis for ball screws in industrial robots under variable and inaccessible working conditions with non-vibration signals.
Adv. Eng. Informatics, 2024
2023
Graph embedding deep broad learning system for data imbalance fault diagnosis of rotating machinery.
Reliab. Eng. Syst. Saf., December, 2023
Federated contrastive prototype learning: An efficient collaborative fault diagnosis method with data privacy.
Knowl. Based Syst., December, 2023
Intelligent machine fault diagnosis with effective denoising using EEMD-ICA- FuzzyEn and CNN.
Int. J. Prod. Res., December, 2023
A novel domain generalization network with multidomain specific auxiliary classifiers for machinery fault diagnosis under unseen working conditions.
Reliab. Eng. Syst. Saf., October, 2023
Actively Imaginative Data Augmentation for Machinery Diagnosis Under Large-Speed-Fluctuation Conditions.
IEEE Trans. Ind. Informatics, July, 2023
Cross-domain augmentation diagnosis: An adversarial domain-augmented generalization method for fault diagnosis under unseen working conditions.
Reliab. Eng. Syst. Saf., June, 2023
Editorial for Special Issue: Machine Health Monitoring and Fault Diagnosis Techniques.
Sensors, April, 2023
Classifier Discrepancy Guided Soft-Weight Adaptation Network for Machinery Fault Diagnosis Under Domain and Category Shift.
IEEE Trans. Instrum. Meas., 2023
A Data Privacy Protection Diagnosis Framework for Multiple Machines Vibration Signals Based on a Swarm Learning Algorithm.
IEEE Trans. Instrum. Meas., 2023
A New Multisource Domain Bearing Fault Diagnosis Method With Adaptive Dual-Domain Obfuscation Weighting Strategy.
IEEE Trans. Instrum. Meas., 2023
Dual Contrastive Learning for Semi-Supervised Fault Diagnosis Under Extremely Low Label Rate.
IEEE Trans. Instrum. Meas., 2023
A Lifelong Learning Method Based on Generative Feature Replay for Bearing Diagnosis With Incremental Fault Types.
IEEE Trans. Instrum. Meas., 2023
Deep hypergraph autoencoder embedding: An efficient intelligent approach for rotating machinery fault diagnosis.
Knowl. Based Syst., 2023
Spiral Complete Coverage Path Planning Based on Conformal Slit Mapping in Multi-connected Domains.
CoRR, 2023
2022
Integration of a Novel Knowledge-Guided Loss Function With an Architecturally Explainable Network for Machine Degradation Modeling.
IEEE Trans. Instrum. Meas., 2022
Multisource Domain Feature Adaptation Network for Bearing Fault Diagnosis Under Time-Varying Working Conditions.
IEEE Trans. Instrum. Meas., 2022
Instantaneous Frequency Synchronized Generalized Stepwise Demodulation Transform for Bearing Fault Diagnosis.
IEEE Trans. Instrum. Meas., 2022
A New Adversarial Domain Generalization Network Based on Class Boundary Feature Detection for Bearing Fault Diagnosis.
IEEE Trans. Instrum. Meas., 2022
IEEE Trans. Instrum. Meas., 2022
Cross-Domain Open-Set Machinery Fault Diagnosis Based on Adversarial Network With Multiple Auxiliary Classifiers.
IEEE Trans. Ind. Informatics, 2022
Adversarial Domain-Invariant Generalization: A Generic Domain-Regressive Framework for Bearing Fault Diagnosis Under Unseen Conditions.
IEEE Trans. Ind. Informatics, 2022
Fault Feature Extractor Based on Bootstrap Your Own Latent and Data Augmentation Algorithm for Unlabeled Vibration Signals.
IEEE Trans. Ind. Electron., 2022
Federated adversarial domain generalization network: A novel machinery fault diagnosis method with data privacy.
Knowl. Based Syst., 2022
Multi-perspective deep transfer learning model: A promising tool for bearing intelligent fault diagnosis under varying working conditions.
Knowl. Based Syst., 2022
Proceedings of the 2022 IEEE International Conference on Prognostics and Health Management, 2022
2021
Dynamic Joint Distribution Alignment Network for Bearing Fault Diagnosis Under Variable Working Conditions.
IEEE Trans. Instrum. Meas., 2021
Fault Diagnosis of a Rotor-Bearing System Under Variable Rotating Speeds Using Two-Stage Parameter Transfer and Infrared Thermal Images.
IEEE Trans. Instrum. Meas., 2021
Enhanced Sparse Regularization Based on Logarithm Penalty and Its Application to Gearbox Compound Fault Diagnosis.
IEEE Trans. Instrum. Meas., 2021
Intelligent Bearing Fault Diagnosis Based on Scaled Ramanujan Filter Banks in Noisy Environments.
IEEE Trans. Instrum. Meas., 2021
Generalized Autocorrelation Method for Fault Detection Under Varying-Speed Working Conditions.
IEEE Trans. Instrum. Meas., 2021
Extended Noise Resistant Correlation Method for Period Estimation of Pseudoperiodic Signals.
IEEE Trans. Instrum. Meas., 2021
A New Multiple Source Domain Adaptation Fault Diagnosis Method Between Different Rotating Machines.
IEEE Trans. Ind. Informatics, 2021
Multi-sensor gearbox fault diagnosis by using feature-fusion covariance matrix and multi-Riemannian kernel ridge regression.
Reliab. Eng. Syst. Saf., 2021
2020
Reliab. Eng. Syst. Saf., 2020
An Intelligent Deep Feature Learning Method With Improved Activation Functions for Machine Fault Diagnosis.
IEEE Access, 2020
Multi-source Unsupervised Domain Adaptation for Machinery Fault Diagnosis under Different Working Conditions.
Proceedings of the 18th IEEE International Conference on Industrial Informatics, 2020
Adversarial multi-domain adaptation for machine fault diagnosis with variable working conditions.
Proceedings of the 18th IEEE International Conference on Industrial Informatics, 2020
2019
Dual-Guidance-Based Optimal Resonant Frequency Band Selection and Multiple Ridge Path Identification for Bearing Fault Diagnosis Under Time-Varying Speeds.
IEEE Access, 2019
IEEE Access, 2019
IEEE Access, 2019
Adaptive Morphological Feature Extraction and Support Vector Regressive Classification for Gearbox Fault Diagnosis.
Proceedings of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 2019
Discovery of a Simplified Index Commonly Used in Various Algorithms for Quantification of Repetitive Transients.
Proceedings of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 2019
2018
Adaptive deep feature learning network with Nesterov momentum and its application to rotating machinery fault diagnosis.
Neurocomputing, 2018
An automatic and robust features learning method for rotating machinery fault diagnosis based on contractive autoencoder.
Eng. Appl. Artif. Intell., 2018
An End-to-End Model Based on Improved Adaptive Deep Belief Network and Its Application to Bearing Fault Diagnosis.
IEEE Access, 2018
2017
Stacked Sparse Autoencoder-Based Deep Network for Fault Diagnosis of Rotating Machinery.
IEEE Access, 2017
A self-adaptive deep belief network with Nesterov momentum for the fault diagnosis of rolling element bearings.
Proceedings of the 2017 International Conference on Deep Learning Technologies, 2017
2016
Sparse representation of gearbox compound fault features by combining Majorization-Minimization algorithm and wavelet bases.
Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2016
2014
Wayside Bearing Fault Diagnosis Based on a Data-Driven Doppler Effect Eliminator and Transient Model Analysis.
Sensors, 2014
2013
A Doppler Transient Model Based on the Laplace Wavelet and Spectrum Correlation Assessment for Locomotive Bearing Fault Diagnosis.
Sensors, 2013