Data Segmentation and Augmentation Methods Based on Raw Data Using Deep Neural Networks Approach for Rotating Machinery Fault Diagnosis. - Zong Meng; Xiaolin Guo; Zuozhou Pan; Dengyun Sun; Shuang Liu (IEEE Access, 2019)

Improvement Motor Imagery EEG Classification Based on Regularized Linear Discriminant Analysis. - Rongrong Fu; Yongsheng Tian; Tiantian Bao; Zong Meng; Peiming Shi (J. Medical Syst., 2019)

Improved adaptive forward-backward matching pursuit algorithm to compressed sensing signal recovery. - Zong Meng; Zuozhou Pan; Ying Shi; Zijun Chen (Multim. Tools Appl., 2019)

2MNet: Multi-sensor and multi-scale model toward accurate fault diagnosis of rolling bearing. - Yang Guan; Zong Meng; Dengyun Sun; Jingbo Liu; Fengjie Fan (Reliab. Eng. Syst. Saf., 2021)

Adaptive energy-constrained variational mode decomposition based on spectrum segmentation and its application in fault detection of rolling bearing. - Jimeng Li; Xing Cheng; Qiang Li; Zong Meng (Signal Process., 2021)

Match-Extracting Chirplet Transform With Application to Bearing Fault Diagnosis. - Quansheng Xu; Jingbo Liu; Yang Guan; Dengyun Sun; Zong Meng (IEEE Trans. Instrum. Meas., 2021)

Fast Fault Diagnosis Method Of Rolling Bearings In Multi-Sensor Measurement Enviroment. - Zuozhou Pan; Zhiping Lin 001; Yuanjin Zheng; Zong Meng (ICASSP, 2022)

Research on fault diagnosis method of MS-CNN rolling bearing based on local central moment discrepancy. - Zong Meng; Wei Cao; Dengyun Sun; Qian Li; Wuxu Ma; Fengjie Fan (Adv. Eng. Informatics, 2022)

Classification and identification of epileptic EEG signals based on signal enhancement. - Jun Jing; Xuewen Pang; Zuozhou Pan; Fengjie Fan; Zong Meng (Biomed. Signal Process. Control., 2022)

Integration of deep adaptation transfer learning and online sequential extreme learning machine for cross-person and cross-position activity recognition. - Quansheng Xu; Xifei Wei; Ruxue Bai; Shiming Li; Zong Meng (Expert Syst. Appl., 2023)

Fractional Fourier Domain Feature Fusion Combining Multichannel Targeting Extreme Learning Machine for Bearing Fault Diagnosis. - Zong Meng; Ruxue Bai; Quansheng Xu; Jimeng Li; Fengjie Fan (IEEE Trans. Instrum. Meas., 2023)

Maximum Cyclic Gini Index Deconvolution for Rolling Bearing Fault Diagnosis. - Zong Meng; Zhaolin Cui; Jingbo Liu; Jimeng Li; Fengjie Fan (IEEE Trans. Instrum. Meas., 2023)

Fractional Fourier and time domain recurrence plot fusion combining convolutional neural network for bearing fault diagnosis under variable working conditions. - Ruxue Bai; Zong Meng; Quansheng Xu; Fengjie Fan (Reliab. Eng. Syst. Saf., 2023)

Rolling bearing remaining useful life prediction based on dilated causal convolutional DenseNet and an exponential model. - Wanmeng Ding; Jimeng Li; Weilin Mao; Zong Meng; Zhongjie Shen (Reliab. Eng. Syst. Saf., 2023)

A parallel GRU with dual-stage attention mechanism model integrating uncertainty quantification for probabilistic RUL prediction of wind turbine bearings. - Lixiao Cao; Hongyu Zhang; Zong Meng; Xueping Wang (Reliab. Eng. Syst. Saf., 2023)

An improved variational mode decomposition method based on spectrum reconstruction and segmentation and its application in rolling bearing fault diagnosis. - Zong Meng; Jing Liu; Jingbo Liu; Jimeng Li; Lixiao Cao; Fengjie Fan; Shancheng Yu (Digit. Signal Process., 2023)

Intelligent fault diagnosis scheme for rolling bearing based on domain adaptation in one dimensional feature matching. - Dengyun Sun; Zong Meng; Yang Guan; Jingbo Liu; Wei Cao; Fengjie Fan (Appl. Soft Comput., 2023)

A novel generation network using feature fusion and guided adversarial learning for fault diagnosis of rotating machinery. - Zong Meng; Huihui He; Wei Cao; Jimeng Li; Lixiao Cao; Jingjing Fan; Meng Zhu; Fengjie Fan (Expert Syst. Appl., 2023)

Condition monitoring of wind turbine based on a novel spatio-temporal feature aggregation network integrated with adaptive threshold interval. - Lixiao Cao; Jie Zhang; Zheng Qian; Zong Meng; Jimeng Li (Adv. Eng. Informatics, 2024)

Fault transfer diagnosis of rolling bearings across different devices via multi-domain information fusion and multi-kernel maximum mean discrepancy. - Jimeng Li; Zhangdi Ye; Jie Gao; Zong Meng; Kai Tong; Shancheng Yu (Appl. Soft Comput., 2024)

A novel diagnostic framework based on vibration image encoding and multi-scale neural network. - Yang Guan; Zong Meng; Jimeng Li; Wei Cao; Dengyun Sun; Jingbo Liu; Fengjie Fan (Expert Syst. Appl., 2024)

HeMTAN: Hybrid task-adapted experts-based multi-task attention network for unseen compound fault decoupling diagnosis of rotating machinery. - Jimeng Li; Wei Wang; Sai Zhong; Zong Meng; Lixiao Cao (Expert Syst. Appl., 2024)

Decoding the task specificity of post-error adjustments: Features and determinants. - Qing Li; Jing Wang; Zong Meng; Yongqiang Chen; Mengke Zhang; Na Hu; Xu Chen; Antao Chen (NeuroImage, 2024)

RUL prediction of rolling bearings across working conditions based on multi-scale convolutional parallel memory domain adaptation network. - Jimeng Li; Weilin Mao; Bixin Yang; Zong Meng; Kai Tong; Shancheng Yu (Reliab. Eng. Syst. Saf., 2024)

A novel multi-task fault detection model embedded with spatio-temporal feature fusion for wind turbine pitch and drive train systems. - Lixiao Cao; Zhiqiang Li; Jimeng Li; Zheng Qian; Zong Meng; Miaomiao Liu (Adv. Eng. Informatics, 2025)

A novel sliding mixing graph contrastive domain adaptation method for fault diagnosis under time-varying speeds. - Kai Chen; Zong Meng; Dengyun Sun; Wei Cao; Yonglei Ren; Weiliang Sun; Jie Wu (Expert Syst. Appl., 2025)

A remaining useful life prediction method of rolling bearings by RSA-BAFT combined with Copula Entropy feature selection. - Zong Meng; Shufan Ma; Wei Cao; Jimeng Li; Lixiao Cao; Fengjie Fan; Xingzhao Wang (Expert Syst. Appl., 2025)

MT-CDGAT: A multi-label diagnosis model for untrained planetary gearbox compound faults based on multi-task cross dynamic graph attention networks. - Lixiao Cao; Yixu Wang; Jimeng Li; Zheng Qian; Zong Meng; Miaomiao Liu (Neurocomputing, 2025)

Fault diagnosis of wind turbine structures with a triaxial vibration dual-branch feature fusion network. - Yang Guan; Zong Meng; Fengshou Gu; Yanling Cao; Dongqin Li; Xiaopeng Miao; Andrew D. Ball (Reliab. Eng. Syst. Saf., 2025)

A Remaining Useful Life Prediction Method for Rolling Bearing Based on TCN-Transformer. - Wei Cao; Zong Meng; Jimeng Li; Jie Wu; Fengjie Fan (IEEE Trans. Instrum. Meas., 2025)

A Novel Cross-Scenario Transferable RUL Prediction Network With Multisource Domain Meta Transfer Learning for Wind Turbine Bearings. - Lixiao Cao; Xueping Wang; Hongyu Zhang; Zong Meng; Jimeng Li; Miaomiao Liu (IEEE Trans. Instrum. Meas., 2025)

Few-Shot Fault Diagnosis of Rolling Bearings Based on Category-Enhanced Siamese Attention Hierarchical-Embedded UNet Network. - Jimeng Li; Jie Gao; Qixian Huang; Zong Meng (IEEE Trans. Instrum. Meas., 2025)

Velocity-Matching Extraction Demodulation Transform for Nonstationary Signal Analysis of Rolling Bearings. - Zong Meng; Yabo Wang; Jingbo Liu; Jimeng Li; Fengjie Fan (IEEE Trans. Instrum. Meas., 2025)

Adaptive Multisynchrosqueezing Transform for Vibration Signal Analysis of Rotating Machinery. - Zong Meng; Zirui Wang; Yabo Wang; Jingbo Liu; Fengjie Fan (IEEE Trans. Instrum. Meas., 2025)

Performance Degradation Assessment for Bearing Based on Angle-Time Cyclostationarity. - Xiaoli Yan; Yuchen Song; Zhetian Wang; Zong Meng; Lide Fang (IEEE Trans. Instrum. Meas., 2025)

A similarity-guided block-structured dictionary learning method for fault feature extraction of rolling bearings. - Jimeng Li; Qingxin Shi; Xilei Guan; Zong Meng (Signal Process., 2026)