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兰州理工大学 [10]

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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 diagnosis of rotor based on Semi-supervised Multi-Graph Joint Embedding 期刊论文 ISA Transactions, 2022 作者: Yuan, Jianhui; Zhao, Rongzhen; He, Tianjing; Chen, Pengfei; Wei, Kongyuan 收藏 \| 浏览/下载：14/0 \| 提交时间：2022/07/20 Clustering algorithms Data reduction Failure analysis Fault detection Graph theory Supervised learning Dimensionality reduction Embeddings Fault data Faults diagnosis High-dimensional Hyper graph Hypergraph structure Rotor systems Sample point Semi-supervised
	Unsupervised domain adaptation of bearing fault diagnosis based on Join Sliced Wasserstein Distance 期刊论文 ISA Transactions, 2022 作者: Chen, Pengfei; Zhao, Rongzhen; He, Tianjing; Wei, Kongyuan; Yang, Qidong 收藏 \| 浏览/下载：8/0 \| 提交时间：2022/07/20 Bearings (machine parts) Deep neural networks Fault detection Large dataset Probability distributions Bearing fault diagnosis Conditional probabilities Domain adaptation Faults diagnosis Mechanical faults diagnosis Mechanical systems Noise interference Pseudo label Sliced wasserstein distances Unsupervised domain adaptation
	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
	Cooling effects of block-scale facade greening and their relationship with urban form 期刊论文 BUILDING AND ENVIRONMENT, 2020, 卷号: 169 作者: Peng, Lilliana L. H.; Jiang, Zhidian; Yang, Xiaoshan; He, Yunfei; Xu, Tianjing 收藏 \| 浏览/下载：12/0 \| 提交时间：2021/11/15
	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; Wu, Yaochun; He, Tianjing 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)

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