Chuan Li
Orcid: 0000-0003-0004-1497Affiliations:
- Dongguan University of Technology, College of Mechanical Engineering, China
- Chongqing Technology and Business University, Chongqing Engineering Laboratory for Detection, Jiangbei, China (former)
According to our database1,
Chuan Li
authored at least 73 papers
between 2006 and 2024.
Collaborative distances:
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Bibliography
2024
Multidomain variance-learnable prototypical network for few-shot diagnosis of novel faults.
J. Intell. Manuf., April, 2024
An Asynchronous Gated Recurrent Network for Estimating Critical Transition of Bearing Deterioration.
IEEE Trans. Ind. Informatics, February, 2024
2023
A novel self-training semi-supervised deep learning approach for machinery fault diagnosis.
Int. J. Prod. Res., December, 2023
Incrementally Contrastive Learning of Homologous and Interclass Features for the Fault Diagnosis of Rolling Element Bearings.
IEEE Trans. Ind. Informatics, November, 2023
Generative adversarial one-shot diagnosis of transmission faults for industrial robots.
Robotics Comput. Integr. Manuf., October, 2023
Sliced Wasserstein cycle consistency generative adversarial networks for fault data augmentation of an industrial robot.
Expert Syst. Appl., July, 2023
Rainfall Forecasting using a Bayesian framework and Long Short-Term Memory Multi-model Estimation based on an hourly meteorological monitoring network. Case of study: Andean Ecuadorian Tropical City.
Earth Sci. Informatics, June, 2023
A novel fault detection method for rotating machinery based on self-supervised contrastive representations.
Comput. Ind., May, 2023
Multiscale reduction clustering of vibration signals for unsupervised diagnosis of machine faults.
Appl. Soft Comput., 2023
Proceedings of the 26th International Conference on Computer Supported Cooperative Work in Design, 2023
2022
Self-Adaptation Graph Attention Network via Meta-Learning for Machinery Fault Diagnosis With Few Labeled Data.
IEEE Trans. Instrum. Meas., 2022
From Anomaly Detection to Novel Fault Discrimination for Wind Turbine Gearboxes With a Sparse Isolation Encoding Forest.
IEEE Trans. Instrum. Meas., 2022
Incremental Novelty Identification From Initially One-Class Learning to Unknown Abnormality Classification.
IEEE Trans. Ind. Electron., 2022
A One-Class Generative Adversarial Detection Framework for Multifunctional Fault Diagnoses.
IEEE Trans. Ind. Electron., 2022
Level-based multi-objective particle swarm optimizer for integrated production scheduling and vehicle routing decision with inventory holding, delivery, and tardiness costs.
Int. J. Prod. Res., 2022
IEEE Intell. Syst., 2022
2021
Theoretical Investigations on Kurtosis and Entropy and Their Improvements for System Health Monitoring.
IEEE Trans. Instrum. Meas., 2021
Coupled Hidden Markov Fusion of Multichannel Fast Spectral Coherence Features for Intelligent Fault Diagnosis of Rolling Element Bearings.
IEEE Trans. Instrum. Meas., 2021
IEEE Trans. Instrum. Meas., 2021
One-Shot Fault Diagnosis of Three-Dimensional Printers Through Improved Feature Space Learning.
IEEE Trans. Ind. Electron., 2021
A manufacturing quality prediction model based on AdaBoost-LSTM with rough knowledge.
Comput. Ind. Eng., 2021
Proceedings of the Neural Computing for Advanced Applications, 2021
2020
A Novel Sparse Echo Autoencoder Network for Data-Driven Fault Diagnosis of Delta 3-D Printers.
IEEE Trans. Instrum. Meas., 2020
Deep Hybrid State Network With Feature Reinforcement for Intelligent Fault Diagnosis of Delta 3-D Printers.
IEEE Trans. Ind. Informatics, 2020
IEEE Trans. Ind. Informatics, 2020
IEEE Trans. Fuzzy Syst., 2020
Fault Diagnosis of Wind Turbine Gearbox Based on the Optimized LSTM Neural Network with Cosine Loss.
Sensors, 2020
Generative Transfer Learning for Intelligent Fault Diagnosis of the Wind Turbine Gearbox.
Sensors, 2020
Knowledge extraction from deep convolutional neural networks applied to cyclo-stationary time-series classification.
Inf. Sci., 2020
Neurocomputing, 2020
Bayesian approach and time series dimensionality reduction to LSTM-based model-building for fault diagnosis of a reciprocating compressor.
Neurocomputing, 2020
A robust dynamic scheduling approach based on release time series forecasting for the steelmaking-continuous casting production.
Appl. Soft Comput., 2020
Forecasting Bus Passenger Flows by Using a Clustering-Based Support Vector Regression Approach.
IEEE Access, 2020
2019
IEEE Trans. Fuzzy Syst., 2019
A comparison of dimension reduction techniques for support vector machine modeling of multi-parameter manufacturing quality prediction.
J. Intell. Manuf., 2019
A hybrid multi-objective genetic local search algorithm for the prize-collecting vehicle routing problem.
Inf. Sci., 2019
Dynamic condition monitoring for 3D printers by using error fusion of multiple sparse auto-encoders.
Comput. Ind., 2019
Flexible Kurtogram for Extracting Repetitive Transients for Prognostics and Health Management of Rotating Components.
IEEE Access, 2019
Generative Adversarial Networks Selection Approach for Extremely Imbalanced Fault Diagnosis of Reciprocating Machinery.
IEEE Access, 2019
2018
Intelligent Fault Diagnosis of Delta 3D Printers Using Attitude Sensors Based on Support Vector Machines.
Sensors, 2018
Advances in intelligent computing for diagnostics, prognostics, and system health management.
J. Intell. Fuzzy Syst., 2018
J. Intell. Fuzzy Syst., 2018
An adaptive genomic difference based genetic algorithm and its application to memetic continuous optimization.
Intell. Data Anal., 2018
A fuzzy transition based approach for fault severity prediction in helical gearboxes.
Fuzzy Sets Syst., 2018
Improved multi-variable grey forecasting model with a dynamic background-value coefficient and its application.
Comput. Ind. Eng., 2018
2017
Microelectron. Reliab., 2017
A Bayesian approach to consequent parameter estimation in probabilistic fuzzy systems and its application to bearing fault classification.
Knowl. Based Syst., 2017
Attribute clustering using rough set theory for feature selection in fault severity classification of rotating machinery.
Expert Syst. Appl., 2017
Automatic feature extraction of time-series applied to fault severity assessment of helical gearbox in stationary and non-stationary speed operation.
Appl. Soft Comput., 2017
Appl. Soft Comput., 2017
2016
Fault Diagnosis for Rotating Machinery Using Vibration Measurement Deep Statistical Feature Learning.
Sensors, 2016
J. Intell. Fuzzy Syst., 2016
A statistical comparison of neuroclassifiers and feature selection methods for gearbox fault diagnosis under realistic conditions.
Neurocomputing, 2016
Eng. Appl. Artif. Intell., 2016
Observer-biased bearing condition monitoring: From fault detection to multi-fault classification.
Eng. Appl. Artif. Intell., 2016
A novel multi-variable grey forecasting model and its application in forecasting the amount of motor vehicles in Beijing.
Comput. Ind. Eng., 2016
Hierarchical feature selection based on relative dependency for gear fault diagnosis.
Appl. Intell., 2016
A methodological framework using statistical tests for comparing machine learning based models applied to fault diagnosis in rotating machinery.
Proceedings of the IEEE Latin American Conference on Computational Intelligence, 2016
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016
2015
Multi-Stage Feature Selection by Using Genetic Algorithms for Fault Diagnosis in Gearboxes Based on Vibration Signal.
Sensors, 2015
Multimodal deep support vector classification with homologous features and its application to gearbox fault diagnosis.
Neurocomputing, 2015
2014
Enhancement of the Wear Particle Monitoring Capability of Oil Debris Sensors Using a Maximal Overlap Discrete Wavelet Transform with Optimal Decomposition Depth.
Sensors, 2014
2013
Continuous development of schemes for parallel computing of the electrostatics in biological systems: Implementation in DelPhi.
J. Comput. Chem., 2013
Verhulst Model of Interval Grey Number Based on Information Decomposing and Model Combination.
J. Appl. Math., 2013
2012
A generalized synchrosqueezing transform for enhancing signal time-frequency representation.
Signal Process., 2012
Highly efficient and exact method for parallelization of grid-based algorithms and its implementation in DelPhi.
J. Comput. Chem., 2012
DelPhi web server v2: incorporating atomic-style geometrical figures into the computational protocol.
Bioinform., 2012
2011
Int. J. Comput. Appl. Technol., 2011
2008
Identification of the Inverse Dynamics Model: A Multiple Relevance Vector Machines Approach.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2008
2006
Next-Day Power Market Clearing Price Forecasting Using Artificial Fish-Swarm Based Neural Network.
Proceedings of the Advances in Neural Networks - ISNN 2006, Third International Symposium on Neural Networks, Chengdu, China, May 28, 2006