Jianbo Yu
Orcid: 0000-0003-3204-2486Affiliations:
- Tongji University, Shanghai, China
According to our database1,
Jianbo Yu
authored at least 93 papers
between 2007 and 2025.
Collaborative distances:
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Bibliography
2025
Multi-Tasks Joint Network for Anomaly Diagnosis and Inconsistent Identification of VRLA Battery in Large Data Center.
IEEE Trans. Ind. Informatics, May, 2025
IEEE Trans. Instrum. Meas., 2025
Crop-paste and diffusion-based semi-supervised segmentation network for metal defect detection.
Knowl. Based Syst., 2025
2024
Incorporate Rotational Speeds Into Deep Neural Network for Machinery Health Monitoring.
IEEE Trans. Ind. Informatics, November, 2024
Deep Morphological Shrinkage Convolutional Autoencoder-Based Feature Learning of Vibration Signals for Gearbox Fault Diagnosis.
IEEE Trans. Instrum. Meas., 2024
Machining Tool Wear Detection and Measurement Based on Edge Extraction and Subpixel Fitting.
IEEE Trans. Instrum. Meas., 2024
A residual autoencoder-based transformer for fault detection of multivariate processes.
Appl. Soft Comput., 2024
2023
IEEE Trans. Cybern., December, 2023
Dynamic convolutional gated recurrent unit attention auto-encoder for feature learning and fault detection in dynamic industrial processes.
Int. J. Prod. Res., November, 2023
A Multisource Domain Adaptation Network for Process Fault Diagnosis Under Different Working Conditions.
IEEE Trans. Ind. Electron., June, 2023
Sparse-Representation-Network-Based Feature Learning of Vibration Signal for Machinery Fault Diagnosis.
IEEE Trans. Ind. Informatics, May, 2023
A Selective Adversarial Adaptation Network for Remaining Useful Life Prediction of Machines Under Different Working Conditions.
IEEE Syst. J., March, 2023
Machine Motion Trajectory Detection Based on Siamese Graph-Attention Adaptive Network.
IEEE Trans. Instrum. Meas., 2023
Adaptive Swarm Decomposition Algorithm for Compound Fault Diagnosis of Rolling Bearings.
IEEE Trans. Instrum. Meas., 2023
Challenges and opportunities of deep learning-based process fault detection and diagnosis: a review.
Neural Comput. Appl., 2023
An exact decomposition method for unrelated parallel machine scheduling with order acceptance and setup times.
Comput. Ind. Eng., 2023
2022
Surface Defect Detection of Steel Strips Based on Anchor-Free Network With Channel Attention and Bidirectional Feature Fusion.
IEEE Trans. Instrum. Meas., 2022
Adaptive Sparse Representation-Based Minimum Entropy Deconvolution for Bearing Fault Detection.
IEEE Trans. Instrum. Meas., 2022
Deep Transfer Network With Adaptive Joint Distribution Adaptation: A New Process Fault Diagnosis Model.
IEEE Trans. Instrum. Meas., 2022
Multiple Granularities Generative Adversarial Network for Recognition of Wafer Map Defects.
IEEE Trans. Ind. Informatics, 2022
Sparse Representation Convolutional Autoencoder for Feature Learning of Vibration Signals and its Applications in Machinery Fault Diagnosis.
IEEE Trans. Ind. Electron., 2022
Sparse one-dimensional convolutional neural network-based feature learning for fault detection and diagnosis in multivariable manufacturing processes.
Neural Comput. Appl., 2022
An integrated method for variation pattern recognition of BIW OCMM online measurement data.
Int. J. Prod. Res., 2022
Unrelated parallel machine scheduling problem with special controllable processing times and setups.
Comput. Oper. Res., 2022
Multi-level features fusion network-based feature learning for machinery fault diagnosis.
Appl. Soft Comput., 2022
Constrained Oversampling: An Oversampling Approach to Reduce Noise Generation in Imbalanced Datasets With Class Overlapping.
IEEE Access, 2022
A weighted nonconvex sparse representation with high-pass filter function for fault diagnosis of rolling bearing.
Proceedings of the 2022 5th International Conference on Sensors, 2022
2021
IEEE Trans. Instrum. Meas., 2021
Convolutional Long Short-Term Memory Autoencoder-Based Feature Learning for Fault Detection in Industrial Processes.
IEEE Trans. Instrum. Meas., 2021
An Adaptive Weighted Adjacent Difference Sparse Representation for Bearing Fault Diagnosis.
IEEE Trans. Instrum. Meas., 2021
Fault Detection of Rolling Bearing Using Sparse Representation-Based Adjacent Signal Difference.
IEEE Trans. Instrum. Meas., 2021
A Deep Domain Adaptative Network for Remaining Useful Life Prediction of Machines Under Different Working Conditions and Fault Modes.
IEEE Trans. Instrum. Meas., 2021
Adaptive Densely Connected Convolutional Auto-Encoder-Based Feature Learning of Gearbox Vibration Signals.
IEEE Trans. Instrum. Meas., 2021
IEEE Trans. Instrum. Meas., 2021
RetinaNet With Difference Channel Attention and Adaptively Spatial Feature Fusion for Steel Surface Defect Detection.
IEEE Trans. Instrum. Meas., 2021
Two-Dimensional Principal Component Analysis-Based Convolutional Autoencoder for Wafer Map Defect Detection.
IEEE Trans. Ind. Electron., 2021
IEEE Trans Autom. Sci. Eng., 2021
Neural Networks, 2021
Multichannel one-dimensional convolutional neural network-based feature learning for fault diagnosis of industrial processes.
Neural Comput. Appl., 2021
Residual attention convolutional autoencoder for feature learning and fault detection in nonlinear industrial processes.
Neural Comput. Appl., 2021
Fault detection and recognition of multivariate process based on feature learning of one-dimensional convolutional neural network and stacked denoised autoencoder.
Int. J. Prod. Res., 2021
Int. J. Prod. Res., 2021
AKRNet: A novel convolutional neural network with attentive kernel residual learning for feature learning of gearbox vibration signals.
Neurocomputing, 2021
Wafer map defect recognition based on deep transfer learning-based densely connected convolutional network and deep forest.
Eng. Appl. Artif. Intell., 2021
Chisel edge wear measurement of high-speed steel twist drills based on machine vision.
Comput. Ind., 2021
Comput. Ind. Eng., 2021
Health condition monitoring of machines based on long short-term memory convolutional autoencoder.
Appl. Soft Comput., 2021
2020
One-Dimensional Residual Convolutional Autoencoder Based Feature Learning for Gearbox Fault Diagnosis.
IEEE Trans. Ind. Informatics, 2020
Variable neighborhood search-based methods for integrated hybrid flow shop scheduling with distribution.
Soft Comput., 2020
Two-dimensional joint local and nonlocal discriminant analysis-based 2D image feature extraction for deep learning.
Neural Comput. Appl., 2020
Knowledge extraction and insertion to deep belief network for gearbox fault diagnosis.
Knowl. Based Syst., 2020
An energy-efficient two-stage hybrid flow shop scheduling problem in a glass production.
Int. J. Prod. Res., 2020
Identical parallel machine scheduling with assurance of maximum waiting time for an emergency job.
Comput. Oper. Res., 2020
An improved formulation and efficient heuristics for the discrete parallel-machine makespan ScheLoc problem.
Comput. Ind. Eng., 2020
Robust (min-max regret) single machine scheduling with interval processing times and total tardiness criterion.
Comput. Ind. Eng., 2020
Comput. Ind. Eng., 2020
2019
Stacked denoising autoencoder-based feature learning for out-of-control source recognition in multivariate manufacturing process.
Qual. Reliab. Eng. Int., 2019
Deep recurrent neural network-based residual control chart for autocorrelated processes.
Qual. Reliab. Eng. Int., 2019
Evolutionary manifold regularized stacked denoising autoencoders for gearbox fault diagnosis.
Knowl. Based Syst., 2019
Neurocomputing, 2019
Stacked convolutional sparse denoising auto-encoder for identification of defect patterns in semiconductor wafer map.
Comput. Ind., 2019
A selective deep stacked denoising autoencoders ensemble with negative correlation learning for gearbox fault diagnosis.
Comput. Ind., 2019
Weighted Self-Regulation Complex Network-Based Variation Modeling and Error Source Diagnosis of Hybrid Multistage Machining Processes.
IEEE Access, 2019
IEEE Access, 2019
Proceedings of the 2019 IEEE International Conference on Industrial Engineering and Engineering Management, 2019
Proceedings of the 2019 IEEE International Conference on Industrial Engineering and Engineering Management, 2019
2018
Sparse Coding Shrinkage in Intrinsic Time-Scale Decomposition for Weak Fault Feature Extraction of Bearings.
IEEE Trans. Instrum. Meas., 2018
State of health prediction of lithium-ion batteries: Multiscale logic regression and Gaussian process regression ensemble.
Reliab. Eng. Syst. Saf., 2018
Tool condition prognostics using logistic regression with penalization and manifold regularization.
Appl. Soft Comput., 2018
2017
Weak Fault Feature Extraction of Rolling Bearings Using Local Mean Decomposition-Based Multilayer Hybrid Denoising.
IEEE Trans. Instrum. Meas., 2017
2015
State-of-Health Monitoring and Prediction of Lithium-Ion Battery Using Probabilistic Indication and State-Space Model.
IEEE Trans. Instrum. Meas., 2015
2014
Health Degradation Detection and Monitoring of Lithium-Ion Battery Based on Adaptive Learning Method.
IEEE Trans. Instrum. Meas., 2014
2013
A modified support vector data description based novelty detection approach for machinery components.
Appl. Soft Comput., 2013
2012
Health Condition Monitoring of Machines Based on Hidden Markov Model and Contribution Analysis.
IEEE Trans. Instrum. Meas., 2012
Local and Nonlocal Preserving Projection for Bearing Defect Classification and Performance Assessment.
IEEE Trans. Ind. Electron., 2012
2011
Online tool wear prediction in drilling operations using selective artificial neural network ensemble model.
Neural Comput. Appl., 2011
Expert Syst. Appl., 2011
Pattern recognition of manufacturing process signals using Gaussian mixture models-based recognition systems.
Comput. Ind. Eng., 2011
A hybrid feature selection scheme and self-organizing map model for machine health assessment.
Appl. Soft Comput., 2011
2010
A neural network ensemble model for on-line monitoring of process mean and variance shifts in correlated processes.
Expert Syst. Appl., 2010
An effective heuristic for flexible job-shop scheduling problem with maintenance activities.
Comput. Ind. Eng., 2010
Proceedings of the International Conference on E-Business and E-Government, 2010
2009
A neural network ensemble-based model for on-line monitoring and diagnosis of out-of-control signals in multivariate manufacturing processes.
Expert Syst. Appl., 2009
Identifying source(s) of out-of-control signals in multivariate manufacturing processes using selective neural network ensemble.
Eng. Appl. Artif. Intell., 2009
Using Minimum Quantization Error chart for the monitoring of process states in multivariate manufacturing processes.
Comput. Ind. Eng., 2009
2008
Neurocomputing, 2008
Intelligent monitoring and diagnosis of manufacturing process using an integrated approach of neural network ensemble and genetic algorithm.
Int. J. Comput. Appl. Technol., 2008
Intelligently reconfigurable manufacturing control system based on knowledge function block.
Int. J. Comput. Appl. Technol., 2008
Intelligent monitoring and diagnosis of manufacturing processes using an integrated approach of KBANN and GA.
Comput. Ind., 2008
An Integrated Framework for Intelligently Reconfigurable Manufacturing Control System Based on Knowledge Function Block.
Proceedings of the Fifth International Conference on Fuzzy Systems and Knowledge Discovery, 2008
2007
An Improved Particle Swarm Optimization for Evolving Feedforward Artificial Neural Networks.
Neural Process. Lett., 2007
Proceedings of the Third International Conference on Natural Computation, 2007