Jinglong Chen
Orcid: 0000-0002-9805-9849
According to our database1,
Jinglong Chen
authored at least 74 papers
between 2015 and 2025.
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Bibliography
2025
Generating HSR Bogie Vibration Signals via Pulse Voltage-Guided Conditional Diffusion Model.
IEEE Trans. Intell. Transp. Syst., January, 2025
Pseudo-label assisted contrastive learning model for unsupervised open-set domain adaptation in fault diagnosis.
Reliab. Eng. Syst. Saf., 2025
Graph embedded patch-sense autoencoder with prior knowledge for multi-component system anomaly detection.
Reliab. Eng. Syst. Saf., 2025
Representations aligned counterfactual domain learning for open-set fault diagnosis under speed transient conditions.
Knowl. Based Syst., 2025
Uncertainty Estimation Pseudo-Label-Guided Source-Free Domain Adaptation for Cross-Domain Remaining Useful Life Prediction in IIoT.
IEEE Internet Things J., 2025
Health prediction under limited degradation data for rocket engine bearings via conditional inference knowledge-enrichment approach.
Adv. Eng. Informatics, 2025
2024
Integrating Misidentification and OOD Detection for Reliable Fault Diagnosis of High-Speed Train Bogie.
IEEE Trans. Intell. Transp. Syst., September, 2024
DecouplingNet: A Stable Knowledge Distillation Decoupling Net for Fault Detection of Rotating Machines Under Varying Speeds.
IEEE Trans. Neural Networks Learn. Syst., August, 2024
Two-Phase Dual-Adversarial Agents With Multivariate Information for Unsupervised Anomaly Detection of IIoT-Edge Devices.
IEEE Internet Things J., July, 2024
Self-Supervised Simple Siamese Framework for Fault Diagnosis of Rotating Machinery With Unlabeled Samples.
IEEE Trans. Neural Networks Learn. Syst., May, 2024
An unsupervised spatiotemporal fusion network augmented with random mask and time-relative information modulation for anomaly detection of machines with multiple measuring points.
Expert Syst. Appl., March, 2024
Graph-Based Model Compression for HSR Bogies Fault Diagnosis at IoT Edge via Adversarial Knowledge Distillation.
IEEE Trans. Intell. Transp. Syst., February, 2024
Knowledge distillation-optimized two-stage anomaly detection for liquid rocket engine with missing multimodal data.
Reliab. Eng. Syst. Saf., January, 2024
Enhancing equipment safeguarding in IIoT: A self-supervised fault diagnosis paradigm based on asymmetric graph autoencoder.
Knowl. Based Syst., 2024
A meta-weighted network equipped with uncertainty estimations for remaining useful life prediction of turbopump bearings.
Expert Syst. Appl., 2024
A synchronization-induced cross-modal contrastive learning strategy for fault diagnosis of electromechanical systems under semi-supervised learning with current signal.
Expert Syst. Appl., 2024
Generative artificial intelligence and data augmentation for prognostic and health management: Taxonomy, progress, and prospects.
Expert Syst. Appl., 2024
2023
Unsupervised Multimodal Anomaly Detection With Missing Sources for Liquid Rocket Engine.
IEEE Trans. Neural Networks Learn. Syst., December, 2023
Domain Discrepancy-Guided Contrastive Feature Learning for Few-Shot Industrial Fault Diagnosis Under Variable Working Conditions.
IEEE Trans. Ind. Informatics, October, 2023
A graph embedded in graph framework with dual-sequence input for efficient anomaly detection of complex equipment under insufficient samples.
Reliab. Eng. Syst. Saf., October, 2023
Image Vis. Comput., August, 2023
An asymmetrical graph Siamese network for one-classanomaly detection of engine equipment with multi-source fusion.
Reliab. Eng. Syst. Saf., July, 2023
Globally Localized Multisource Domain Adaptation for Cross-Domain Fault Diagnosis With Category Shift.
IEEE Trans. Neural Networks Learn. Syst., June, 2023
A variational transformer for predicting turbopump bearing condition under diverse degradation processes.
Reliab. Eng. Syst. Saf., April, 2023
A Position-Free Signal Transformer via Multiband Inner Relationship Extraction for Understanding Information Flow of Machinery Diagnosis.
IEEE Trans. Instrum. Meas., 2023
Intelligent Fault Quantitative Identification via the Improved Deep Deterministic Policy Gradient (DDPG) Algorithm Accompanied With Imbalanced Sample.
IEEE Trans. Instrum. Meas., 2023
One-stage self-supervised momentum contrastive learning network for open-set cross-domain fault diagnosis.
Knowl. Based Syst., 2023
2022
Toward Small Sample Challenge in Intelligent Fault Diagnosis: Attention-Weighted Multidepth Feature Fusion Net With Signals Augmentation.
IEEE Trans. Instrum. Meas., 2022
A Dual-Guided Adaptive Decomposition Method of Fault Information and Fault Sensitivity for Multi-Component Fault Diagnosis Under Varying Speeds.
IEEE Trans. Instrum. Meas., 2022
A Novel Multisensor Orthogonal Attention Fusion Network for Multibolt Looseness State Recognition Under Small Sample.
IEEE Trans. Instrum. Meas., 2022
Similarity Metric-Based Metalearning Network Combining Prior Metatraining Strategy for Intelligent Fault Detection Under Small Samples Prerequisite.
IEEE Trans. Instrum. Meas., 2022
Prior Knowledge-Augmented Self-Supervised Feature Learning for Few-Shot Intelligent Fault Diagnosis of Machines.
IEEE Trans. Ind. Electron., 2022
A multi-head attention network with adaptive meta-transfer learning for RUL prediction of rocket engines.
Reliab. Eng. Syst. Saf., 2022
A soft-target difference scaling network via relational knowledge distillation for fault detection of liquid rocket engine under multi-source trouble-free samples.
Reliab. Eng. Syst. Saf., 2022
Efficient temporal flow Transformer accompanied with multi-head <i>probsparse</i> self-attention mechanism for remaining useful life prognostics.
Reliab. Eng. Syst. Saf., 2022
A multi-module generative adversarial network augmented with adaptive decoupling strategy for intelligent fault diagnosis of machines with small sample.
Knowl. Based Syst., 2022
Cross-domain intelligent bearing fault diagnosis under class imbalanced samples via transfer residual network augmented with explicit weight self-assignment strategy based on meta data.
Knowl. Based Syst., 2022
Meta-learning as a promising approach for few-shot cross-domain fault diagnosis: Algorithms, applications, and prospects.
Knowl. Based Syst., 2022
High-temperature augmented neighborhood metric learning for cross-domain fault diagnosis with imbalanced data.
Knowl. Based Syst., 2022
Multi-expert Attention Network with Unsupervised Aggregation for long-tailed fault diagnosis under speed variation.
Knowl. Based Syst., 2022
Imbalance fault diagnosis under long-tailed distribution: Challenges, solutions and prospects.
Knowl. Based Syst., 2022
Temporal convolution-based sorting feature repeat-explore network combining with multi-band information for remaining useful life estimation of equipment.
Knowl. Based Syst., 2022
CFs-focused intelligent diagnosis scheme via alternative kernels networks with soft squeeze-and-excitation attention for fast-precise fault detection under slow & sharp speed variations.
Knowl. Based Syst., 2022
Make the Rocket Intelligent at IoT Edge: Stepwise GAN for Anomaly Detection of LRE With Multisource Fusion.
IEEE Internet Things J., 2022
IEEE Internet Things J., 2022
Intelligent Fault Quantitative Identification for Industrial Internet of Things (IIoT) via a Novel Deep Dual Reinforcement Learning Model Accompanied With Insufficient Samples.
IEEE Internet Things J., 2022
Prototype augmented network with metric-mixed under limited samples for mechanical intelligent fault recognition.
Appl. Soft Comput., 2022
2021
SASLN: Signals Augmented Self-Taught Learning Networks for Mechanical Fault Diagnosis Under Small Sample Condition.
IEEE Trans. Instrum. Meas., 2021
QSCGAN: An Un-Supervised Quick Self-Attention Convolutional GAN for LRE Bearing Fault Diagnosis Under Limited Label-Lacked Data.
IEEE Trans. Instrum. Meas., 2021
A Novel Multitask Adversarial Network via Redundant Lifting for Multicomponent Intelligent Fault Detection Under Sharp Speed Variation.
IEEE Trans. Instrum. Meas., 2021
A Supervised Framework for Recognition of Liquid Rocket Engine Health State Under Steady-State Process Without Fault Samples.
IEEE Trans. Instrum. Meas., 2021
Layer Regeneration Network With Parameter Transfer and Knowledge Distillation for Intelligent Fault Diagnosis of Bearing Using Class Unbalanced Sample.
IEEE Trans. Instrum. Meas., 2021
Deep Feature Generating Network: A New Method for Intelligent Fault Detection of Mechanical Systems Under Class Imbalance.
IEEE Trans. Ind. Informatics, 2021
A Small Sample Focused Intelligent Fault Diagnosis Scheme of Machines via Multimodules Learning With Gradient Penalized Generative Adversarial Networks.
IEEE Trans. Ind. Electron., 2021
Intelligent fault diagnosis under small sample size conditions via Bidirectional InfoMax GAN with unsupervised representation learning.
Knowl. Based Syst., 2021
Similarity-based meta-learning network with adversarial domain adaptation for cross-domain fault identification.
Knowl. Based Syst., 2021
Proceedings of the IEEE International Conference on Acoustics, 2021
2020
A Deep Learning Network via Shunt-Wound Restricted Boltzmann Machines Using Raw Data for Fault Detection.
IEEE Trans. Instrum. Meas., 2020
Multiple degradation mode analysis via gated recurrent unit mode recognizer and life predictors for complex equipment.
Comput. Ind., 2020
Hybrid attribute conditional adversarial denoising autoencoder for zero-shot classification of mechanical intelligent fault diagnosis.
Appl. Soft Comput., 2020
Towards Intelligent Fault Diagnosis under Small Sample Condition via A Signals Augmented Semi-supervised Learning Framework.
Proceedings of the 18th IEEE International Conference on Industrial Informatics, 2020
Sequence Adaptation Adversarial Network for Remaining Useful Life Prediction Using Small Data Set.
Proceedings of the 18th IEEE International Conference on Industrial Informatics, 2020
2019
A Novel Deep Learning Network via Multiscale Inner Product With Locally Connected Feature Extraction for Intelligent Fault Detection.
IEEE Trans. Ind. Informatics, 2019
Gated recurrent unit based recurrent neural network for remaining useful life prediction of nonlinear deterioration process.
Reliab. Eng. Syst. Saf., 2019
Degradation feature extraction using multi-source monitoring data via logarithmic normal distribution based variational auto-encoder.
Comput. Ind., 2019
An Adversarial Learning Framework for Zero-shot Fault Recognition of Mechanical Systems.
Proceedings of the 17th IEEE International Conference on Industrial Informatics, 2019
2018
LiftingNet: A Novel Deep Learning Network With Layerwise Feature Learning From Noisy Mechanical Data for Fault Classification.
IEEE Trans. Ind. Electron., 2018
2017
Hyper-parameter optimization based nonlinear multistate deterioration modeling for deterioration level assessment and remaining useful life prognostics.
Reliab. Eng. Syst. Saf., 2017
Design and implementation of data communication module based on plugin mode in configuration software.
Proceedings of the 9th International Conference on Advanced Infocomm Technology, 2017
2016
Quantitative Index and Abnormal Alarm Strategy Using Sensor-Dependent Vibration Data for Blade Crack Identification in Centrifugal Booster Fans.
Sensors, 2016
Multi-domain description method for bearing fault recognition in varying speed condition.
Proceedings of the IECON 2016, 2016
Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2016
Improved VMD for feature visualization to identify wheel set bearing fault of high speed locomotive.
Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2016
2015
Fault Diagnosis of Demountable Disk-Drum Aero-Engine Rotor Using Customized Multiwavelet Method.
Sensors, 2015