游科顺｜南华大学｜学者主页

2026

Robust rotating machinery diagnosis from Single-Source heterogeneous signals under imbalanced and noisy conditions

Ke-Shun You, Ying-Kui Gu, Yanhui Lin, Hai-Dong Shao, Ya-Jun Wang

Engineering Science and Technology, an International Journal

DOI

2026

A physics-constrained multimodal LLM for fault diagnosis of pressurized water reactor coolant systems with imbalanced and under-sampled data

Ke-Shun You, Haidong Shao, Zhichao Chen, Jie Yang, Xian Du, Yanghui Lin, Yajun Wang

Journal of Industrial Information Integration

DOI

2026

A rolling bearing remaining useful life prediction model based on multi-source heterogeneous features with temperature-guided

Ying-Kui Gu, Puzhou Wang, Zi-Xin Cheng, Ke-Shun You, Guangqi Qiu

Measurement science and technology

DOI

2026

A liquid-impulse neural network model based on heterogeneous fusion of multimodal information for interpretable rotating machinery fault diagnosis

Ke-Shun You, Ying-Kui Gu, Haidong Shao, Ya-Jun Wang

Mechanical systems and signal processing

DOI

2025

DTMPI-DIVR: A digital twins for multi-margin physical information via dynamic interaction of virtual and real sound-vibration signals for bearing fault diagnosis without real fault samples

Keshun You, Chenlu Liu, Yanghui Lin, Guangqi Qiu, Yingku Gu

Expert Systems With Applications，Vol. 292

DOI

2025

A sound-vibration physical-information fusion constraint-guided deep learning method for rolling bearing fault diagnosis

Keshun You, Puzhou Wang, Peng Huang, Yingkui Gu

Reliability Engineering & System Safety，Vol. 253

DOI

2025

声-振物理信息约束引导深度学习的球磨机滚动轴承故障诊断方法

游科顺

《江西理工大学》

2025

A novel physical constraint-guided quadratic neural networks for interpretable bearing fault diagnosis under zero-fault sample

Ke-Shun You, Ying-Kui Gu, Yanghui Lin, Ya-Jun Wang

Nondestructive Testing and Evaluation

DOI

2024

Optimizing prior distribution parameters for probabilistic prediction of remaining useful life using deep learning

Keshun You, Guangqi Qiu, Yingkui Gu

Reliability Engineering & System Safety，Vol. 242

DOI

2024

A 3-D Attention-Enhanced Hybrid Neural Network for Turbofan Engine Remaining Life Prediction Using CNN and BiLSTM Models

Ke-Shun You, Guang-Qi Qiu, Ying-Kui Gu

IEEE Sensors Journal

DOI

2024

An adaptive acoustic signal reconstruction and fault diagnosis method for rolling bearings based on SSDAE–MobileViT

Ying-Kui Gu, Puzhou Wang, Yin Li, Ke-Shun You, Guang-Qi Qiu

Measurement science and technology

DOI

2024

A performance-interpretable intelligent fusion of sound and vibration signals for bearing fault diagnosis via dynamic CAME

Ke-Shun You, Zeng-Wei Lian, Ying-Kui Gu

Nonlinear dynamics

DOI

2024

Toward Efficient and Interpretative Rolling Bearing Fault Diagnosis via Quadratic Neural Network With Bi-LSTM

Ke-Shun You, Puzhou Wang, Yingkui Gu

IEEE Internet of Things Journal

DOI

2024

A novel rolling bearing fault diagnosis method based on time-series fusion transformer with interpretability analysis

Ke-Shun You, Zeng-Wei Lian, Ronghua Chen, Ying-Kui Gu

Nondestructive Testing and Evaluation

DOI

2023

An efficient lightweight neural network using BiLSTM-SCN-CBAM with PCA-ICEEMDAN for diagnosing rolling bearing faults

Ke-Shun You, Guang-Qi Qiu, Yingkui Gu

Measurement science and technology

DOI

2023

Remaining useful life prediction of lithium-ion batteries using EM-PF-SSA-SVR with gamma stochastic process

Ke-Shun You, Guang-Qi Qiu, Yingkui Gu

Measurement science and technology

DOI

2022

Rolling Bearing Fault Diagnosis Using Hybrid Neural Network with Principal Component Analysis

Ke-Shun You, Guang-Qi Qiu, Yingkui Gu

Italian National Conference on Sensors

DOI

A physical soft-constraint interpretability-based multimodal deep learning model for small-sample fault diagnosis of pressurized water reactor coolant systems in nuclear power plants

Ke-Shun You, Hai-Dong Shao, Ya-Jun Wang, Yanhui Lin, Ying-Kui Gu

Expert systems with applications

DOI

游科顺

精选作品

期刊论文

Robust rotating machinery diagnosis from Single-Source heterogeneous signals under imbalanced and noisy conditions

A physics-constrained multimodal LLM for fault diagnosis of pressurized water reactor coolant systems with imbalanced and under-sampled data

A rolling bearing remaining useful life prediction model based on multi-source heterogeneous features with temperature-guided

A liquid-impulse neural network model based on heterogeneous fusion of multimodal information for interpretable rotating machinery fault diagnosis

DTMPI-DIVR: A digital twins for multi-margin physical information via dynamic interaction of virtual and real sound-vibration signals for bearing fault diagnosis without real fault samples

A sound-vibration physical-information fusion constraint-guided deep learning method for rolling bearing fault diagnosis

声-振物理信息约束引导深度学习的球磨机滚动轴承故障诊断方法

A novel physical constraint-guided quadratic neural networks for interpretable bearing fault diagnosis under zero-fault sample

Optimizing prior distribution parameters for probabilistic prediction of remaining useful life using deep learning

A 3-D Attention-Enhanced Hybrid Neural Network for Turbofan Engine Remaining Life Prediction Using CNN and BiLSTM Models

An adaptive acoustic signal reconstruction and fault diagnosis method for rolling bearings based on SSDAE–MobileViT

A performance-interpretable intelligent fusion of sound and vibration signals for bearing fault diagnosis via dynamic CAME

Toward Efficient and Interpretative Rolling Bearing Fault Diagnosis via Quadratic Neural Network With Bi-LSTM

A novel rolling bearing fault diagnosis method based on time-series fusion transformer with interpretability analysis

An efficient lightweight neural network using BiLSTM-SCN-CBAM with PCA-ICEEMDAN for diagnosing rolling bearing faults

Remaining useful life prediction of lithium-ion batteries using EM-PF-SSA-SVR with gamma stochastic process

Rolling Bearing Fault Diagnosis Using Hybrid Neural Network with Principal Component Analysis

A physical soft-constraint interpretability-based multimodal deep learning model for small-sample fault diagnosis of pressurized water reactor coolant systems in nuclear power plants

研究方向