Multi-Objective Machining Parameters Optimization for Chatter-Free Milling Process Considering Material Removal Rate and Surface Location Error. - Congying Deng; Yi Feng; Jianguo Miao; Ying Ma; Bo Wei (IEEE Access, 2019)

Reliability analysis of chatter stability for milling process system with uncertainties based on neural network and fourth moment method. - Congying Deng; Jianguo Miao; Ying Ma; Bo Wei; Yi Feng (Int. J. Prod. Res., 2020)

Prediction of Tool Point Frequency Response Functions within Machine Tool Work Volume Considering the Position and Feed Direction Dependence. - Congying Deng; Yi Feng; Jie Shu; Zhiyu Huang; Qian Tang (Symmetry, 2020)

Chatter Stability Prediction and Process Parameters' Optimization of Milling Considering Uncertain Tool Information. - Lijun Lin; Mingge He; Qingyuan Wang 003; Congying Deng (Symmetry, 2021)

FEM Simulation Data-driven Fault Diagnosis Method for Bearing based on Improved Dynamic Adversarial Adaptive Network with Attention. - Congying Deng; Huiling Ding; Meiling Miao (SAFEPROCESS, 2023)

Health Indicator Construction for Milling Tool Wear Monitoring With Multi-sensor Fusion. - Shuhao Zhang; Bin Zhang; Congying Deng (SAFEPROCESS, 2023)

Fault Diagnosis Method for Imbalanced Data Based on Multi-Signal Fusion and Improved Deep Convolution Generative Adversarial Network. - Congying Deng; Zihao Deng; Sheng Lu; Mingge He; Jianguo Miao; Ying Peng (Sensors, 2023)

Interactive channel attention for rotating component fault detection with strong noise and limited data. - Jianguo Miao; Congying Deng; Heng Zhang; Qiang Miao (Appl. Soft Comput., 2023)

Efficient stability prediction of milling process with arbitrary tool-holder combinations based on transfer learning. - Congying Deng; Jielin Tang; Jianguo Miao; Yang Zhao; Xiang Chen; Sheng Lu (J. Intell. Manuf., 2023)

Efficient Prediction of Stability Boundaries in Milling Considering the Variation of Tool Features and Workpiece Materials. - Huijuan Sun; Huiling Ding; Congying Deng; Kaixiang Xiong (Sensors, 2023)

Multi-fidelity modeling and neural network supported prediction of position and tool overhang length-dependent milling stability with limited labeled data. - Congying Deng; Yi Dong; Jianguo Miao; Feng Tan (Comput. Ind. Eng., 2024)

Boosting efficient attention assisted cyclic adversarial auto-encoder for rotating component fault diagnosis under low label rates. - Jianguo Miao; Zihao Deng; Congying Deng; Chong Chen (Eng. Appl. Artif. Intell., 2024)

Improved milling stability analysis for chatter-free machining parameters planning using a multi-fidelity surrogate model and transfer learning with limited experimental data. - Congying Deng; Jielin Tang; Sheng Lu; Ying Ma; Lijun Lin; Jianguo Miao (Int. J. Prod. Res., 2024)

Semi-supervised ensemble fault diagnosis method based on adversarial decoupled auto-encoder with extremely limited labels. - Congying Deng; Zihao Deng; Jianguo Miao (Reliab. Eng. Syst. Saf., 2024)

Co-Kriging model-based multi-fidelity regression for refining milling stability predictions of variable tool overhang length using limited experimental data. - Congying Deng; Huiling Ding; Jianguo Miao; Feng Tan (Int. J. Prod. Res., 2025)

Domain adaptation method based on pseudo-label dual-constraint targeted decoupling network for cross-machine fault diagnosis. - Congying Deng; Hongyang Tian; Jianguo Miao; Zihao Deng (Reliab. Eng. Syst. Saf., 2025)