相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。Variational Inference: A Review for Statisticians
David M. Blei et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2017)
Deep Learning Enabled Fault Diagnosis Using Time-Frequency Image Analysis of Rolling Element Bearings
David Verstraete et al.
SHOCK AND VIBRATION (2017)
Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification
Chen Lu et al.
SIGNAL PROCESSING (2017)
Principal component analysis: a review and recent developments
Ian T. Jolliffe et al.
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES (2016)
Rolling element bearing diagnostics using the Case Western Reserve University data: A benchmark study
Wade A. Smith et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2015)
Structural damage assessment using linear approximation with maximum entropy and transmissibility data
V. Meruane et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2015)
Recent advances in time-frequency analysis methods for machinery fault diagnosis: A review with application examples
Zhipeng Feng et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2013)
A review on empirical mode decomposition in fault diagnosis of rotating machinery
Yaguo Lei et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2013)
PRIOR AND POSTERIOR ROBUST STOCHASTIC PREDICTIONS FOR DYNAMICAL SYSTEMS USING PROBABILITY LOGIC
James L. Beck et al.
INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION (2013)
Fault detection based on Kernel Principal Component Analysis
Viet Ha Nguyen et al.
ENGINEERING STRUCTURES (2010)
A Comparative Study on the Local Mean Decomposition and Empirical Mode Decomposition and Their Applications to Rotating Machinery Health Diagnosis
Yanxue Wang et al.
JOURNAL OF VIBRATION AND ACOUSTICS-TRANSACTIONS OF THE ASME (2010)
Decision tree and PCA-based fault diagnosis of rotating machinery
Weixiang Sun et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2007)
Reducing the dimensionality of data with neural networks
G. E. Hinton et al.
SCIENCE (2006)
Fault detection and identification of nonlinear processes based on kernel PCA
SW Choi et al.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2005)
Gear fault detection using artificial neural networks and support vector machines with genetic algorithms
B Samanta
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2004)
Artificial neural networks and support vector machines with genetic algorithm for bearing fault detection
B Samanta et al.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2003)
Non-linear principal components analysis with application to process fault detection
F Jia et al.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE (2000)
分享论文
