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浏览/检索结果: 共19条，第1-10条 帮助 限定条件 发表日期：2021     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择发表日期升序发表日期降序提交时间升序提交时间降序题名升序题名降序作者升序作者降序 Improved VMD-FRFT based on initial center frequency for early fault diagnosis of rolling element bearing 期刊论文 MEASUREMENT SCIENCE AND TECHNOLOGY, 2021, 卷号: 32, 期号: 11 作者:  Chen, Guangyi;  Yan, Changfeng;  Meng, Jiadong;  Wang, Huibin;  Wu, Lixiao 收藏  |  浏览/下载：11/0  |  提交时间：2021/10/14 bearing fault detection  initial center frequency  periodic impulses  reciprocal of spectral autocorrelation smoothness index  variational mode decomposition-fractional Fourier transform   Bearing Defect Detection with Unsupervised Neural Networks 期刊论文 SHOCK AND VIBRATION, 2021, 卷号: 2021 作者:  Xu, Jianqiao;  Zuo, Zhaolu;  Wu, Danchao;  Li, Bing;  Li, Xiaoni 收藏  |  浏览/下载：14/0  |  提交时间：2021/11/01 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   基于深度学习的多工况滚动轴承故障诊断算法研究 学位论文 沈阳: 中国科学院沈阳自动化研究所, 2021 作者:  孙仕鑫 收藏  |  浏览/下载：6/0  |  提交时间：2021/06/12 变负载  噪声环境  多工况  健康状态  卷积神经网络   Fault Monitoring Method of Wind Turbine Main Bearing 期刊论文 Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis, 2021, 卷号: 41, 期号: 2, 页码: 341-347 and 415 作者:  Zheng, Yuqiao;  Wei, Jianfeng;  Zhu, Kai;  Dong, Bo 收藏  |  浏览/下载：6/0  |  提交时间：2022/02/17 Bearings (machine parts)  Forecasting  Linear regression  Monitoring  Sliding mode control  Statistics  Support vector machines  Support vector regression  Wind turbines  Change of temperatures  Combination forecasting models  Determination coefficients  Mean and standard deviations  Multiple linear regression models  Multivariate linear regression model  Sliding window methods  Support vector machine regressions   Fault feature extraction of rolling bearing integrating KPCA and t-SNE 期刊论文 Zhendong Gongcheng Xuebao/Journal of Vibration Engineering, 2021, 卷号: 34, 期号: 2, 页码: 431-440 作者:  Wang, Wang-Wang;  Deng, Lin-Feng;  Zhao, Rong-Zhen;  Wu, Yao-Chun 收藏  |  浏览/下载：64/0  |  提交时间：2022/02/17 Clustering algorithms  Data mining  Extraction  Feature extraction  Frequency domain analysis  Nearest neighbor search  Stochastic systems  Time domain analysis  Fault feature extractions  Feature extraction methods  Global and local structures  High dimensional feature  K-nearest neighbor classifier  Kernel principal component analyses (KPCA)  Rolling bearing vibration  Stochastic neighbor embedding   Multi-branch convolutional neural network with generalized shaft orbit for fault diagnosis of active magnetic bearing-rotor system 期刊论文 MEASUREMENT, 2021, 卷号: 171, 页码: 11 作者:  Yan Xunshi;  张陈安4);  Liu Y(刘洋) 收藏  |  浏览/下载：22/0  |  提交时间：2021/03/30 Fault diagnosis  Convolutional neural network  Active magnetic bearing  Multi-sensor fusion  Shaft orbit   Initial fault time estimation of rolling element bearing by backtracking strategy, improved VMD and infogram 期刊论文 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY, 2021, 卷号: 35, 期号: 2, 页码: 425-437 作者:  Babiker, Abdalla;  Yan, Changfeng;  Li, Qiang;  Meng, Jiadong;  Wu, Lixiao 收藏  |  浏览/下载：8/0  |  提交时间：2021/03/12 EMPIRICAL MODE DECOMPOSITION  FEATURE-EXTRACTION  SPECTRAL KURTOSIS  DIAGNOSIS  KURTOGRAM  SPEED   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   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：13/0  |  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)