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兰州理工大学 [36]

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	An early composite fault feature extraction method of bearing based on square envelope spectrum negentropy criterion 期刊论文 Zhendong yu Chongji/Journal of Vibration and Shock, 2022, 卷号: 41, 期号: 8, 页码: 179-187 作者: Chen, Peng; Zhao, Xiaoqiang 收藏 \| 浏览/下载：8/0 \| 提交时间：2022/06/20 Failure analysis Fault detection Spectrum analysis Bearing Composite fault Early composite fault diagnose Envelope spectra Faults diagnosis Grasshopper optimization algorithm Negentropy Optimization algorithms Square envelope spectrum negentropy Swarm decomposition
	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
	Online monitoring and fault diagnosis for uneven length batch process based on multi-way orthogonal enhanced neighborhood preserving embedding 期刊论文 ASIA-PACIFIC JOURNAL OF CHEMICAL ENGINEERING, 2022, 卷号: 17, 期号: 3 作者: Zhang, Yan; Zhao, Xiaoqiang; Hui, Yongyong; Liu, Kai 收藏 \| 浏览/下载：6/0 \| 提交时间：2022/04/21 batch process fault diagnosis neighborhood preserving embedding orthogonal basis functions uneven length
	Average Descent Rate Singular Value Decomposition and Two-Dimensional Residual Neural Network for Fault Diagnosis of Rotating Machinery 期刊论文 IEEE Transactions on Instrumentation and Measurement, 2022, 卷号: 71 作者: Liang, Haopeng; Cao, Jie; Zhao, Xiaoqiang 收藏 \| 浏览/下载：9/0 \| 提交时间：2022/06/20 Deep neural networks Failure analysis Fault detection Feature extraction Gears Rotating machinery Average descent rate singular value decomposition Convolutional neural network Deep learning Faults diagnosis Features extraction Gramian angular difference field Gramians Neural-networks Noise measurements Two-dimensional Two-dimensional residual neural network Vibration
	A new fault feature extraction method of rotating machinery based on finite sample function 期刊论文 Noise and Vibration Worldwide, 2021, 卷号: 52, 期号: 6, 页码: 137-144 作者: Miao, Feng; Zhao, Rongzhen 收藏 \| 浏览/下载：4/0 \| 提交时间：2021/06/03 Extraction Feature extraction Rotating machinery Sampling Composite fault Fault feature extractions Higher efficiency Kernel function Rub impact fault Separation performance Super-Gaussian sources 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
	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 Method of Rolling Bearing Fault Diagnose Based on Double Sparse Dictionary and Deep Belief Network 期刊论文 IEEE Access, 2020, 卷号: 8, 期号: 7, 页码: 116239-116253 作者: Junfeng Guo; Pengfei Zheng 收藏 \| 浏览/下载：6/0 \| 提交时间：2020/11/11 Sparse representation double sparse dictionary deep belief network (DBN) bearing fault diagnosis feature extraction.
	Dynamic characteristics of compound fault in deep groove ball bearing 期刊论文 Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology, 2020, 卷号: 52, 期号: 1, 页码: 133-140 作者: Wang, Kai; Yan, Changfeng; Wang, Fengtao; Chang, Binquan; Wu, Lixiao 收藏 \| 浏览/下载：11/0 \| 提交时间：2020/11/14 Condition monitoring Deep groove ball bearings Dynamic models Vibration analysis Bearing condition monitoring Compound faults Dynamic characteristics Excitation mechanisms Fault characteristics Hertz contact theory Slipping Time varying
	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

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