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兰州理工大学 [24]

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	Knowledge enhanced ensemble method for remaining useful life prediction under variable working conditions 期刊论文 RELIABILITY ENGINEERING & SYSTEM SAFETY, 2024, 卷号: 242, 页码: 13 作者: Li, Yuan; Li, Jingwei; Wang, Huanjie; Liu, Chengbao; Tan, Jie 收藏 \| 浏览/下载：6/0 \| 提交时间：2024/02/22 Remaining useful life Ensemble learning Attention mechanism Convolutional neural network Transfer learning
	Failure mechanism tracing of the crankshaft for reciprocating High-Pressure plunger pump 期刊论文 Engineering Failure Analysis, 2022, 卷号: 141 作者: Dong, Jie; Zhao, Shendan; Wang, Zhongkai; Wei, Liejiang; Bian, Hailong 收藏 \| 浏览/下载：29/0 \| 提交时间：2022/08/09 Crankshafts Fatigue of materials Fracture Outages Pumps Failure forms Failure mechanism Fatigue failures High pressure Plunger pumps Power machinery Reciprocating plunger pump Stress amplitudes Transition fillet Typical failures
	Health condition monitoring of bearings based on multifractal spectrum feature with modified empirical mode decomposition-multifractal detrended fluctuation analysis 期刊论文 STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL, 2022 作者: Chen, Guangyi; Yan, Changfeng; Meng, Jiadong; Wang, Zonggang; Wu, Lixiao 收藏 \| 浏览/下载：27/0 \| 提交时间：2022/03/01 Empirical mode decomposition-multifractal detrended fluctuation analysis scaling exponent health condition monitoring step-moving window multifractal spectrum feature deterministic random separation
	Remaining Useful Life prediction of rolling bearings based on risk assessment and degradation state coefficient 期刊论文 ISA Transactions, 2022 作者: Li, Qiang; Yan, Changfeng; Chen, Guangyi; Wang, Huibin; Li, Hongkun 收藏 \| 浏览/下载：21/0 \| 提交时间：2022/07/20 Condition based maintenance Economic and social effects Forecasting Frequency domain analysis Genetic algorithms Health Health risks Roller bearings Singular value decomposition Degradation state Degradation state coefficient Genetic algorithm-support vector regression Health indicators Mode decomposition Modified health indicator Remaining useful lives Risks assessments Support vector regressions Variational mode decomposition-singular value decomposition
	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：12/0 \| 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
	Experimental study on thermal deformation and clamping force characteristics of hydraulic spool valve 期刊论文 ENGINEERING FAILURE ANALYSIS, 2021, 卷号: 129 作者: Qian-peng, Chen; Hong, Ji; Hui-hui, Xing; Hong-ke, Zhao 收藏 \| 浏览/下载：5/0 \| 提交时间：2021/10/14 Hydraulic spool valve Reliability Thermal deformation Clamping force Measurement experiments
	Fast Fault Diagnosis System Based on Data Mining AR Algorithm 会议论文 Nanjing, China, 2021-10 作者: Yu Yahan; Du Juan; Ren Guanghao; Tan Yao; Wang Jian 收藏 \| 浏览/下载：1/0 \| 提交时间：2023/06/02
	A Regularized LSTM Method for Predicting Remaining Useful Life of Rolling Bearings 期刊论文 International Journal of Automation and Computing, 2021, 卷号: 18, 期号: 4, 页码: 581-593 作者: Zhao-Hua Liu 收藏 \| 浏览/下载：14/0 \| 提交时间：2021/07/20 Deep learning fault diagnosis fault prognosis long and short time memory network (LSTM) rolling bearing rotating machinery regularization remaining useful life prediction (RUL) recurrent neural network (RNN)
	Research on Rotating Machinery Fault Diagnosis Method Based on Energy Spectrum Matrix and Adaptive Convolutional Neural Network 期刊论文 PROCESSES, 2021, 卷号: 9, 期号: 1, 页码: 1-25 作者: Liu YY(刘意杨); Yang YS(杨友胜); Feng TY(冯铁); Sun Y(孙懿); Zhang XJ(张雪健) 收藏 \| 浏览/下载：11/0 \| 提交时间：2021/02/14 hierarchical fault diagnosis energy spectrum matrix dynamic adjustment of the learning rate convolutional neural network rotating machinery
	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：64/0 \| 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

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