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Congying Deng
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2020 – today
- 2024
- [j12]Congying Deng, Yi Dong, Jianguo Miao, Feng Tan:
Multi-fidelity modeling and neural network supported prediction of position and tool overhang length-dependent milling stability with limited labeled data. Comput. Ind. Eng. 194: 110409 (2024) - [j11]Jianguo Miao, Zihao Deng, Congying Deng
, Chong Chen:
Boosting efficient attention assisted cyclic adversarial auto-encoder for rotating component fault diagnosis under low label rates. Eng. Appl. Artif. Intell. 133: 108499 (2024) - [j10]Congying Deng, Jielin Tang, Sheng Lu, Ying Ma, Lijun Lin, Jianguo Miao:
Improved milling stability analysis for chatter-free machining parameters planning using a multi-fidelity surrogate model and transfer learning with limited experimental data. Int. J. Prod. Res. 62(4): 1126-1143 (2024) - [j9]Congying Deng, Zihao Deng, Jianguo Miao:
Semi-supervised ensemble fault diagnosis method based on adversarial decoupled auto-encoder with extremely limited labels. Reliab. Eng. Syst. Saf. 242: 109740 (2024) - 2023
- [j8]Jianguo Miao
, Congying Deng, Heng Zhang
, Qiang Miao
:
Interactive channel attention for rotating component fault detection with strong noise and limited data. Appl. Soft Comput. 138: 110171 (2023) - [j7]Congying Deng, Jielin Tang, Jianguo Miao, Yang Zhao, Xiang Chen
, Sheng Lu
:
Efficient stability prediction of milling process with arbitrary tool-holder combinations based on transfer learning. J. Intell. Manuf. 34(5): 2263-2279 (2023) - [j6]Congying Deng, Zihao Deng, Sheng Lu
, Mingge He, Jianguo Miao, Ying Peng:
Fault Diagnosis Method for Imbalanced Data Based on Multi-Signal Fusion and Improved Deep Convolution Generative Adversarial Network. Sensors 23(5): 2542 (2023) - [j5]Huijuan Sun, Huiling Ding, Congying Deng, Kaixiang Xiong:
Efficient Prediction of Stability Boundaries in Milling Considering the Variation of Tool Features and Workpiece Materials. Sensors 23(21): 8954 (2023) - [c2]Congying Deng, Huiling Ding, Meiling Miao:
FEM Simulation Data-driven Fault Diagnosis Method for Bearing based on Improved Dynamic Adversarial Adaptive Network with Attention. SAFEPROCESS 2023: 1-6 - [c1]Shuhao Zhang, Bin Zhang, Congying Deng:
Health Indicator Construction for Milling Tool Wear Monitoring With Multi-sensor Fusion. SAFEPROCESS 2023: 1-5 - 2021
- [j4]Lijun Lin, Mingge He, Qingyuan Wang
, Congying Deng:
Chatter Stability Prediction and Process Parameters' Optimization of Milling Considering Uncertain Tool Information. Symmetry 13(6): 1071 (2021) - 2020
- [j3]Congying Deng, Jianguo Miao, Ying Ma, Bo Wei, Yi Feng:
Reliability analysis of chatter stability for milling process system with uncertainties based on neural network and fourth moment method. Int. J. Prod. Res. 58(9): 2732-2750 (2020) - [j2]Congying Deng, Yi Feng
, Jie Shu, Zhiyu Huang, Qian Tang:
Prediction of Tool Point Frequency Response Functions within Machine Tool Work Volume Considering the Position and Feed Direction Dependence. Symmetry 12(7): 1073 (2020)
2010 – 2019
- 2019
- [j1]Congying Deng
, Yi Feng, Jianguo Miao, Ying Ma, Bo Wei:
Multi-Objective Machining Parameters Optimization for Chatter-Free Milling Process Considering Material Removal Rate and Surface Location Error. IEEE Access 7: 183823-183837 (2019)
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last updated on 2024-08-29 21:55 CEST by the dblp team
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