Study on Hankel matrix-based SVD and its application in rolling element bearing fault diagnosis
Based on the traditional theory of singular value decomposition (SVD), singular values (SVs)
and ratios of neighboring singular values (NSVRs) are introduced to the feature extraction of …
and ratios of neighboring singular values (NSVRs) are introduced to the feature extraction of …
Roller bearing fault diagnosis method based on chemical reaction optimization and support vector machine
Support vector machine (SVM) parameter optimization has always been a demanding task
in machine learning. The chemical reaction optimization (CRO) method is an established …
in machine learning. The chemical reaction optimization (CRO) method is an established …
Fault diagnosis of rolling bearing based on PSO and continuous Gaussian mixture HMM
G Liao, H Zhu, K Liu, JW Liao - 2015 2nd International …, 2015 - atlantis-press.com
As the hidden Markov model (HMM) has a strong ability of time sequence modeling, the
continuous Gaussian mixture HMM is used to establish a model base of the rolling bearing …
continuous Gaussian mixture HMM is used to establish a model base of the rolling bearing …
Simulation-based approach for detection of bearing defects through continuous wavelet transform
D Paliwal, A Choudhury… - International Journal of …, 2015 - inderscienceonline.com
Rolling element bearings are the heart of modern industrial machineries, thus, an early
detection of budding faults in bearings is essential to avoid ruinous machine failures. This …
detection of budding faults in bearings is essential to avoid ruinous machine failures. This …
Two general architectures for intelligent machine performance degradation assessment
Y Xu, A Xu, T Xie - Shock and Vibration, 2015 - Wiley Online Library
Markov model is of good ability to infer random events whose likelihood depends on
previous events. Based on this theory, hidden Markov model serves as an extension of …
previous events. Based on this theory, hidden Markov model serves as an extension of …