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	A remaining useful life prediction method based on time–frequency images of the mechanical vibration signals 期刊论文 Measurement: Journal of the International Measurement Confederation, 2022, 卷号: 202 作者: Du, Xianjun; Jia, Wenchao; Yu, Ping; Shi, Yaoke; Cheng, Shengyi 收藏 \| 浏览/下载：32/0 \| 提交时间：2022/09/22 Convolution Forecasting Preventive maintenance Rotating machinery Vibrations (mechanical) Wavelet transforms Attention mechanisms Continuous Wavelet Transform Convolutional neural network Degradation trend Feature map Remaining useful life predictions Rolling bearings Spectral feature Time frequency Time–frequency spectral feature map
	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：14/0 \| 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
	Health Condition Identification of Rolling Element Bearing Based on Gradient of Features Matrix and MDDCs-MRSVD 期刊论文 IEEE Transactions on Instrumentation and Measurement, 2022, 卷号: 71, 页码: 1-1 作者: Meng, Jiadong; Yan, Changfeng; Wang, Zonggang; Wen, Tao; Chen, Guangyi 收藏 \| 浏览/下载：13/0 \| 提交时间：2022/08/09 Condition based maintenance Condition monitoring Health Interactive computer systems Roller bearings Feature matrices Gradient Health condition Initial faults Maximal difference of detail component in multi-resolution singular value decomposition algorithm Monitoring indicators Real Time system Rolling Element Bearing Singular value decomposition algorithms Vibration
	Fault Classification Method of Rolling Bearing Based on Cloud Theory and ReliefHF 期刊论文 Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis, 2021, 卷号: 41, 期号: 4, 页码: 667-672 作者: Ma, Sencai; Zhao, Rongzhen; Wu, Yaochun; DENG, Linfeng 收藏 \| 浏览/下载：11/0 \| 提交时间：2022/02/17 Knowledge based systems Classification accuracy Classification methods Cloud classification Cloud distributions Fault classification Noise resistance Rolling bearings Weight coefficients
	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
	Rolling Bearing Fault Identification Based on Quantum-Behaved Particle Swarm Optimization and Multi-scale Permutation Entropy 期刊论文 Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis, 2021, 卷号: 41, 期号: 1, 页码: 62-68 作者: Wang, Wangwang; Deng, Linfeng; Zhao, Rongzhen; Zhang, Aihua 收藏 \| 浏览/下载：19/0 \| 提交时间：2021/04/12 Clustering algorithms Entropy Fuzzy clustering Particle swarm optimization (PSO) Signal reconstruction Ensemble empirical mode decompositions (EEMD) Fault feature extractions Fault recognition Intrinsic Mode functions Permutation entropy Quantum-behaved particle swarm optimization Rolling bearings Vibration signal
	Rolling Bearing Fault Diagnosis Based on One-Dimensional Dilated Convolution Network With Residual Connection 期刊论文 IEEE ACCESS, 2021, 卷号: 9, 页码: 31078-31091 作者: Liang, Haopeng; Zhao, Xiaoqiang 收藏 \| 浏览/下载：21/0 \| 提交时间：2021/03/12 Convolution Fault diagnosis Feature extraction Rolling bearings Vibrations Kernel Load modeling Different load domains different noisy environments dilated convolution one-dimensional convolution neural network rolling bearing fault diagnosis residual connection
	A New Method of Fault Feature Extraction Based on Hierarchical Dispersion Entropy 期刊论文 Shock and Vibration, 2021, 卷号: 2021 作者: Chen, Peng; Zhao, Xiaoqiang; Jiang, Hongmei 收藏 \| 浏览/下载：21/0 \| 提交时间：2021/04/12 Dispersions Entropy Extraction Failure analysis Feature extraction Gaussian noise (electronic) Nearest neighbor search Roller bearings Signal processing White noise Fault diagnosis method Fault feature extractions Feature information Gaussian white noise K-nearest neighbor classifiers (KNN) Low frequency band Rolling bearings Vibration signal
	Rolling Bearing Fault Diagnosis Based on One-Dimensional Dilated Convolution Network with Residual Connection 期刊论文 IEEE Access, 2021, 卷号: 9, 页码: 31078-31091 作者: Liang, Haopeng; Zhao, Xiaoqiang 收藏 \| 浏览/下载：63/0 \| 提交时间：2021/04/12 Convolution Failure analysis Fault detection Multilayer neural networks Time domain analysis Connection structures Convolution neural network Feature learning Noisy environment Residual structure Rolling bearings Time-domain signal Weight coefficients
	A novel classification method based on ICGOA-KELM for fault diagnosis of rolling bearing 期刊论文 Applied Intelligence, 2020, 卷号: 50, 期号: 无, 页码: 2833-2847 作者: Peng Chen; Xiaoqiang Zhao; Qixian Zhu 收藏 \| 浏览/下载：14/0 \| 提交时间：2020/11/06 Chaotic systems Computer aided diagnosis Damage detection Failure analysis Fault detection Machine learning Optimization Extreme learning machine Fault detection and classification Global searching ability Heuristic optimization algorithms ICGOA- KELM Intrinsic Mode functions Optimization algorithms Rolling bearings

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