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浏览/检索结果: 共8条，第1-8条 帮助 限定条件 发表日期：2021    专题：兰州理工大学    第一署名单位    第一作者单位    通讯作者单位     已选(0)清除 条数/页：5101520253035404550556065707580859095100   排序方式：请选择作者升序作者降序题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序 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   Mechanical Fault Diagnosis Method Based on Multi-sensor Signal Feature Fusion Using Deep Convolutional Neural Network 期刊论文 Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis, 2021, 卷号: 41, 期号: 2, 页码: 362-369 and 416 作者:  Wu, Yaochun;  Zhao, Rongzhen;  Jin, Wuyin;  He, Tianjing;  Wu, Jie 收藏  |  浏览/下载：16/0  |  提交时间：2022/02/17 Complex networks  Convolution  Convolutional neural networks  Deep neural networks  Failure analysis  Fault detection  Fault classification  Feature representation  Hierarchical fusions  Mechanical fault diagnosis  Multi-sensor information fusion  Multisensor data fusion  One-dimensional features  Softmax regressions   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   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   Fault diagnosis of rotor based on Local-Global Balanced Orthogonal Discriminant Projection 期刊论文 Measurement: Journal of the International Measurement Confederation, 2021, 卷号: 168 作者:  Shi, Mingkuan;  Zhao, Rongzhen;  Wu, Yaochun;  He, Tianjing 收藏  |  浏览/下载：17/0  |  提交时间：2020/11/14 Fault detection  Frequency domain analysis  Nearest neighbor search  Rotating machinery  Time domain analysis  Application examples  Complex characteristics  Discriminant informations  High dimensional feature  Inter-class distance  K-nearest neighbor method  Structure information  Time frequency domain   Observer-based fault detection and diagnosis for the nonlinear stochastic distribution systems 期刊论文 Journal of Computational Methods in Sciences and Engineering, 2021, 卷号: 21, 期号: 1, 页码: 213-221 作者:  Yi, Qu 收藏  |  浏览/下载：3/0  |  提交时间：2021/06/03 Probability density function  Probability distributions  Rational functions  Stochastic systems  Adaptive tuning rules  Convergence and stability  Fault detection and diagnosis  Observer-based fault detection and diagnosis  Probability density functions (PDFs)  Rational square roots  Simulation example  Stochastic distribution systems   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   An Intelligent Optimization-Based Particle Filter for Fault Diagnosis 期刊论文 IEEE ACCESS, 2021, 卷号: 9, 页码: 87839-87848 作者:  Cao, Zheng;  Du, Xianjun 收藏  |  浏览/下载：3/0  |  提交时间：2021/10/14 Mathematical model  Fault diagnosis  Wind power generation  Search problems  Doubly fed induction generators  Wind turbines  Particle filters  Fault diagnosis  detection and isolation  particle filter (PF)  beetle swarm antennae search (BSAS) algorithm  doubly fed induction generator (DFIG)