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兰州理工大学 [7]

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	Intelligent fault diagnosis of rolling bearing based on novel CNN model considering data imbalance 期刊论文 APPLIED INTELLIGENCE, 2022 作者: Xing, Ziyang; Zhao, Rongzhen; Wu, Yaochun; He, Tianjing 收藏 \| 浏览/下载：7/0 \| 提交时间：2022/04/21 Deep learning Imbalanced data Fault diagnosis Loss function
	Fault Identification of Rolling Bearing Using Variational Mode Decomposition Multiscale Permutation Entropy and Adaptive GG Clustering 期刊论文 SHOCK AND VIBRATION, 2021, 卷号: 2021 作者: He, Tianjing; Zhao, Rongzhen; Wu, Yaochun; Yang, Chao 收藏 \| 浏览/下载：2/0 \| 提交时间：2021/10/14
	Mechanical Fault Diagnosis Method Based on Multi-sensor Signal Feature Fusion Using Deep Convolutional Neural Network 期刊论文 Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis, 2021, 卷号: 41, 期号: 2, 页码: 362-369 and 416 作者: Wu, Yaochun; Zhao, Rongzhen; Jin, Wuyin; He, Tianjing; Wu, Jie 收藏 \| 浏览/下载：16/0 \| 提交时间：2022/02/17 Complex networks Convolution Convolutional neural networks Deep neural networks Failure analysis Fault detection Fault classification Feature representation Hierarchical fusions Mechanical fault diagnosis Multi-sensor information fusion Multisensor data fusion One-dimensional features Softmax regressions
	Intelligent fault diagnosis of rolling bearings using a semi-supervised convolutional neural network 期刊论文 Applied Intelligence, 2021, 卷号: 51, 期号: 4, 页码: 2144-2160 作者: Wu, Yaochun; Zhao, Rongzhen; Jin, Wuyin; He, Tianjing; Ma, Sencai 收藏 \| 浏览/下载：3/0 \| 提交时间：2021/06/03 Convolution Deep learning Failure analysis Fault detection Learning systems Roller bearings Semi-supervised learning Vibration analysis Class probabilities Diagnosis performance Intelligent fault diagnosis Inter-class distance Learning methods Maximum margin criterions Rolling bearings Vibration signal
	Fault diagnosis of rotor based on Local-Global Balanced Orthogonal Discriminant Projection 期刊论文 Measurement: Journal of the International Measurement Confederation, 2021, 卷号: 168 作者: Shi, Mingkuan; Zhao, Rongzhen; Wu, Yaochun; He, Tianjing 收藏 \| 浏览/下载：17/0 \| 提交时间：2020/11/14 Fault detection Frequency domain analysis Nearest neighbor search Rotating machinery Time domain analysis Application examples Complex characteristics Discriminant informations High dimensional feature Inter-class distance K-nearest neighbor method Structure information Time frequency domain
	Rolling Bearing Fault Diagnosis Using a Deep Convolutional Autoencoding Network and Improved Gustafson-Kessel Clustering 期刊论文 Shock and Vibration, 2020, 卷号: 2020 作者: Wu, Yaochun; Zhao, Rongzhen; Jin, Wuyin; Deng, Linfeng; He, Tianjing 收藏 \| 浏览/下载：9/0 \| 提交时间：2022/02/18 Clustering algorithms Convolution Convolutional neural networks Deep learning Deep neural networks Failure analysis Roller bearings Stochastic systems
	A Kind of Faults Knowledge Discovery Pattern by Means of Rough Set Theory 会议论文 Huddersfield, United kingdom, September 3, 2019 - September 5, 2019 作者: Zhao, Rongzhen 收藏 \| 浏览/下载：2/0 \| 提交时间：2020/11/15 Big data Classification (of information) Condition monitoring Data structures Expert systems Knowledge acquisition Machinery Data classification Data structure model Data-driven methods Engineering project Equivalent relation Inclusion relation Knowledge conversion Rough set theory (RST)
	Controllable Chain-Length for Covalent Sulfur-Carbon Materials Enabling Stable and High-Capacity Sodium Storage 期刊论文 Advanced Energy Materials, 2019, 卷号: 9, 期号: 9, 页码: - 作者: Wu, Tianjing; Jing, Mingjun; Yang, Li; Zou, Guogiong; Hou, Hongshuai 收藏 \| 浏览/下载：12/0 \| 提交时间：2019/12/03 bridge‐bond covalent sulfur–carbon electrochemistry Na–S batteries
	Anions induced evolution of Co3X4 (X = O, S, Se) as sodium-ion anodes: The influences of electronic structure, morphology, electrochemical property 期刊论文 Nano Energy, 2018, 卷号: 48, 页码: 617-629 作者: Ge, Peng; Zhang, Chenyang; Hou, Hongshuai; Wu, Buke; Zhou, Liang 收藏 \| 浏览/下载：3/0 \| 提交时间：2019/12/04 Co3X4 Evolution Sodium-ion battery Anodes Electrochemistry
	Dual Functions of Potassium Antimony(III)-Tartrate in Tuning Antimony/Carbon Composites for Long-Life Na-Ion Batteries 期刊论文 Advanced Functional Materials, 2018, 卷号: 28, 期号: 10, 页码: - 作者: Wu, Tianjing; Zhang, Chenyang; Hou, Hongshuai; Ge, Peng; Zou, Guoqiang 收藏 \| 浏览/下载：19/0 \| 提交时间：2019/12/03 dual‐carbon‐modified structures Sb/C Sb?O?C bonds self‐thermal reduction sodium‐ion batteries

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