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湖南大学 [5]
重庆大学 [4]
北京航空航天大学 [3]
沈阳自动化研究所 [3]
清华大学 [2]
兰州理工大学 [2]
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期刊论文 [14]
会议论文 [7]
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Uncertainty-aware Deep Learning: A Promising Tool for Trustworthy Fault Diagnosis
期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 6, 页码: 1317-1330
作者:
Jiaxin Ren
;
Jingcheng Wen
;
Zhibin Zhao
;
Ruqiang Yan
;
Xuefeng Chen
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2024/05/22
Out-of-distribution detection
traceability analysis
trustworthy fault diagnosis
uncertainty quantification
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
Hidden Markov model based rotate vector reducer fault detection using acoustic emissions
期刊论文
INTERNATIONAL JOURNAL OF SENSOR NETWORKS, 2020, 卷号: 32, 期号: 2, 页码: 116-125
作者:
An HB(安海博)
;
Liang W(梁炜)
;
Zhang YL(张吟龙)
;
Tan JD(谈金东)
收藏
  |  
浏览/下载:31/0
  |  
提交时间:2020/03/01
RV
rotate vector reducer
fault detection
HMM
hidden Markov model
AE
acoustic emission
Optimizing SVM's parameters based on backtracking search optimization algorithm for gear fault diagnosis.
期刊论文
Journal of Vibroengineering, 2019, 卷号: Vol.21 No.1, 页码: 66-81
作者:
Vantrong Thai
;
Junsheng Cheng
;
Viethung Nguyen
;
Phuonganh Daothi
收藏
  |  
浏览/下载:5/0
  |  
提交时间:2019/12/13
artificial neural networks
backtracking search optimization algorithm
fault detection
gears
signal processing
Fault diagnosis of gearbox based on the nonlinear output frequency response functions and PNN
会议论文
Vibroengineering Procedia
作者:
Zhang, X.
;
Wang, Z.
;
Lu, C.
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2019/12/30
Condition monitoring
Failure analysis
Frequency response
Gears
Neural networks
Abnormal conditions
Complex nonlinear system
Feature extraction methods
Frequency domain approaches
Gearbox
Non-linear output frequency response function
Probabilistic neural networks
The NOFRFs
Fault detection
Fault Diagnosis of Gear Based on Singular Value Decomposition and RBF Neural Network
会议论文
2017 2ND INTERNATIONAL CONFERENCE ON FRONTIERS OF SENSORS TECHNOLOGIES (ICFST), 2017-01-01
作者:
Zhang, Qi[1]
;
Zhao, Wei[2]
;
Xiao, Shun Gen[3]
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2019/04/24
singular value decomposition
RBF neural network
gears fault diagnosis
wavelet packet
A new fault diagnosis algorithm for helical gears rotating at low speed using an optical encoder
期刊论文
2016, 卷号: 93, 页码: 449-459
作者:
Shao, Yimin[1]
;
Su, Daizhong[2]
;
Al-Habaibeh, Amin[3]
;
Yu, Wennian[1]
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  |  
浏览/下载:2/0
  |  
提交时间:2019/11/29
Multidimensional Tensor-Based Inductive Thermography With Multiple Physical Fields for Offshore Wind Turbine Gear Inspection.
期刊论文
IEEE Transactions on Industrial Electronics, 2016, 卷号: Vol.63 No.10, 页码: 6305-6315
作者:
Gao, B
;
He, YZ
;
Woo, WL
;
Tian, GY
;
Liu, J
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2019/12/31
Eddy currents
Fatigue
Fault diagnosis
gears
Heating
imaging inspection
inductive thermography
Inspection
multidimensional tensor model
thermo optical flow
Gears fault diagnosis method using ensemble empirical mode decomposition energy entropy assisted acroa-rbf neural network
期刊论文
Journal of Computational and Theoretical Nanoscience, 2016, 卷号: Vol.13 No.5, 页码: 3222-3232
作者:
Le, Duc Hieu
;
Cheng, Junsheng
;
Yang, Yu
;
Tran, Trong Nhan
;
Pham, Van Thoan
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2019/12/31
Fault diagnosis of gears based on local mean decomposition combing with kurtosis
期刊论文
JOURNAL OF VIBROENGINEERING, 2014, 卷号: 16, 页码: 2639-2648
作者:
Pan, Qiang
;
He, Tian
;
Shan, Yingchun
;
Liu, Xiandong
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2020/01/06
local mean decomposition
gear
fault diagnosis
Hilbert transform
kurtosis
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