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兰州理工大学 [37]

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	Rolling bearing fault diagnosis by Markov transition field and multi-dimension convolutional neural network 期刊论文 Measurement Science and Technology, 2022, 卷号: 33, 期号: 11 作者: Lei, Chunli; Xue, Linlin; Jiao, Mengxuan; Zhang, Huqiang; Shi, Jiashuo 收藏 \| 浏览/下载：33/0 \| 提交时间：2022/09/22 Chemical activation Convolution Convolutional neural networks Fault detection Neural network models Roller bearings Activation functions Condition Convolutional neural network E-rectified linear unit activation function Faults diagnosis Linear units Markov transition field Multi dimensions Multi-dimension attention Transition fields
	An intelligent diagnosis method of rolling bearing based on multi-scale residual shrinkage convolutional neural network 期刊论文 Measurement Science and Technology, 2022, 卷号: 33, 期号: 8 作者: Zhao, Xiaoqiang; Zhang, Yazhou 收藏 \| 浏览/下载：13/0 \| 提交时间：2022/06/20 Convolutional neural networks Deep learning Failure (mechanical) Failure analysis Fault detection Roller bearings Shrinkage Bearing fault diagnosis Convolutional neural network Intelligent diagnosis methods Multi-scale residual shrinkage convolutional neural network Multi-scales Noise environments Rolling bearings Separable convolution Variable operating condition Vibration signal
	Stochastic resonance in image denoising as an alternative to traditional methods and deep learning 期刊论文 NONLINEAR DYNAMICS, 2022 作者: Shen, Mengen; Yang, Jianhua; Jiang, Wenbo; Sanjuan, Miguel A. F.; Zheng, Yuqiao 收藏 \| 浏览/下载：13/0 \| 提交时间：2022/07/19 Blind image denoising Monostable system Stochastic resonance Deep learning BM3D
	Intelligent Fault Identification Method Based on Convolutional Neural Network for Imbalanced Data 期刊论文 Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis, 2022, 卷号: 42, 期号: 2, 页码: 299-307 作者: Wu, Yaochun; Zhao, Rongzhen; Jin, Wuyin; Xing, Ziyang 收藏 \| 浏览/下载：13/0 \| 提交时间：2022/06/20 Convolutional neural networks Machinery Class spaces Convolutional neural network Fault identifications Identification method Imbalanced data Intelligent fault diagnosis Min-max Min-max objective func-tion Net work Objective functions
	Research on condition monitoring and fault diagnosis of intelligent copper ball production lines based on big data 期刊论文 IET Collaborative Intelligent Manufacturing, 2022, 卷号: 4, 期号: 1, 页码: 45-57 作者: Zhang, Zhongke; Li, Zhao; Zhao, Changzhong 收藏 \| 浏览/下载：15/0 \| 提交时间：2022/04/21 Big data Display devices Failure analysis Fault detection Light emission Metadata Program debugging Trees (mathematics) Virtual private networks Cloud platforms Condition monitoring and faults diagnosis Electronics materials Fault prediction Faults diagnosis Manufacturing industries On condition monitoring Production line Window control center configuration Windows control centers
	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 based on SPBO-SDAE and transformer neural network for rotating machinery 期刊论文 MEASUREMENT, 2022, 卷号: 188 作者: Du, Xianjun; Jia, Liangliang; Ul Haq, Izaz 收藏 \| 浏览/下载：30/0 \| 提交时间：2022/03/01 Fault diagnosis Rotating machinery Hyper parameter optimization Feature self-extraction Transformer neural network Self attention mechanism
	Intelligent identification of incipient rolling bearing faults based on VMD and PCA-SVM 期刊论文 ADVANCES IN MECHANICAL ENGINEERING, 2022, 卷号: 14, 期号: 1 作者: Deng, Linfeng; Zhang, Aihua; Zhao, Rongzhen 收藏 \| 浏览/下载：23/0 \| 提交时间：2022/03/01 Incipient rolling bearing faults intelligent identification energy and kurtosis variational mode decomposition principal component analysis support vector machine
	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
	An Intelligent Optimization-Based Particle Filter for Fault Diagnosis 期刊论文 IEEE ACCESS, 2021, 卷号: 9, 页码: 87839-87848 作者: Cao, Zheng; Du, Xianjun 收藏 \| 浏览/下载：3/0 \| 提交时间：2021/10/14 Mathematical model Fault diagnosis Wind power generation Search problems Doubly fed induction generators Wind turbines Particle filters Fault diagnosis detection and isolation particle filter (PF) beetle swarm antennae search (BSAS) algorithm doubly fed induction generator (DFIG)

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