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	Label propagation-based unsupervised domain adaptation for intelligent fault diagnosis 期刊论文 JOURNAL OF INTELLIGENT MANUFACTURING, 2023, 页码: 18 作者: Wang, Huanjie; Li, Yuan; Bai, Xiwei; Li, Jingwei; Tan, Jie 收藏 \| 浏览/下载：2/0 \| 提交时间：2023/11/17 Intelligent diagnosis Rotating machinery Label propagation Subpopulation shift Unsupervised domain adaptation
	Intelligent fault diagnosis of train bearing based on ISTOA-VMD and SE-WDCNN 期刊论文 JOURNAL OF VIBRATION AND CONTROL, 2023, 页码: 12 作者: He, Deqiang; Zou, Xueyan; Jin, Zhenzhen; Yan, Jingren; Ren, Chonghui 收藏 \| 浏览/下载：0/0 \| 提交时间：2023/12/07 intelligent fault diagnosis train bearing improved sooty tern optimization algorithm variational mode decomposition deep convolutional neural network
	Influence of the Moho surface distribution on the oil and gas basins in China seas and adjacent areas 期刊论文 ACTA OCEANOLOGICA SINICA, 2023, 卷号: 42, 期号: 3, 页码: 167-188 作者: Zhang, Yimi; Wang, Wanyin; Li, Linzhi; Luo, Xingang; Wang, Dingding 收藏 \| 浏览/下载：1/0 \| 提交时间：2023/12/13 China Seas and adjacent areas Moho surface oil and gas basins
	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
	Cross-Level fusion for rotating machinery fault diagnosis under compound variable working conditions 期刊论文 MEASUREMENT, 2022, 卷号: 199, 页码: 7 作者: Wang, Sihan; Wang, Dazhi; Kong, Deshan; Li, Wenhui; Wang, Huanjie 收藏 \| 浏览/下载：15/0 \| 提交时间：2022/07/25 Intelligent fault diagnosis Few-shot learning Anti-noise Compound faults Working condition variation
	Real-time identification of performance degradation stages of rolling element bearings by RVCFI 期刊论文 Measurement Science and Technology, 2022, 卷号: 33, 期号: 8 作者: Meng, Jiadong; Yan, Changfeng; Wen, Tao; Wang, Zonggang; Chen, Guangyi 收藏 \| 浏览/下载：13/0 \| 提交时间：2022/06/20 Condition based maintenance Condition monitoring Degradation Singular value decomposition Degradation stages Envelope spectra Fault time Initial faults Monitoring indicators Performance degradation Performance degradation stage Rate of variation coefficient of fused indicator Rolling Element Bearing Variation coefficient
	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
	Separation method of rolling bearing compound fault characteristics based on Improved harmonic wavelet packet decomposition and fast ICA 期刊论文 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, 2022, 卷号: 36, 期号: 7, 页码: 3263-3276 作者: Huang, Hua; Xue, Wenhu; Pang, Qianzhi 收藏 \| 浏览/下载：15/0 \| 提交时间：2022/07/19 Compound fault Fast ICA Improved harmonic wavelet packet decomposition Rolling bearing fault diagnosis
	Few-shot multiscene fault diagnosis of rolling bearing under compound variable working conditions 期刊论文 IET CONTROL THEORY AND APPLICATIONS, 2022, 页码: 12 作者: Wang, Sihan; Wang, Dazhi; Kong, Deshan; Li, Wenhui; Wang, Jiaxing 收藏 \| 浏览/下载：16/0 \| 提交时间：2022/07/25
	Adversarial domain adaptation convolutional neural network for intelligent recognition of bearing faults 期刊论文 Measurement: Journal of the International Measurement Confederation, 2022, 卷号: 195 作者: Wu, Yaochun; Zhao, Rongzhen; Ma, Hongru; He, Qiang; Du, Shaohua 收藏 \| 浏览/下载：30/0 \| 提交时间：2022/04/21 Convolution Machinery Bearing Bearing fault Convolutional neural network Domain adaptation Fault recognition Intelligent fault recognition Intelligent recognition Recognition methods Target domain Varying working conditions

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