An overview of time-based and condition-based maintenance in industrial application
R Ahmad, S Kamaruddin - Computers & industrial engineering, 2012 - Elsevier
This paper presents an overview of two maintenance techniques widely discussed in the
literature: time-based maintenance (TBM) and condition-based maintenance (CBM). The …
literature: time-based maintenance (TBM) and condition-based maintenance (CBM). The …
Fault detection analysis in rolling element bearing: A review
P Gupta, MK Pradhan - Materials Today: Proceedings, 2017 - Elsevier
Rolling element bearings are very critical components of rotating machines and the
presence of defects in the bearing may lead to failure of machines. Hence, early …
presence of defects in the bearing may lead to failure of machines. Hence, early …
Convolutional neural network-based hidden Markov models for rolling element bearing fault identification
S Wang, J Xiang, Y Zhong, Y Zhou - Knowledge-Based Systems, 2018 - Elsevier
Vibration signals of faulty rolling element bearings usually exhibit non-linear and non-
stationary characteristics caused by the complex working environment. It is difficult to …
stationary characteristics caused by the complex working environment. It is difficult to …
Domain adaptive deep belief network for rolling bearing fault diagnosis
C Che, H Wang, X Ni, Q Fu - Computers & Industrial Engineering, 2020 - Elsevier
As the essential components of rotating machines, rolling bearings always operate in
variable working conditions and suffer from different failure modes. To address the issue of …
variable working conditions and suffer from different failure modes. To address the issue of …
Review of condition monitoring of rolling element bearing using vibration analysis and other techniques
C Malla, I Panigrahi - Journal of Vibration Engineering & Technologies, 2019 - Springer
Background Different types of machines having rotary component are linked together in
process industries, to perform the process of manufacturing. The failure of any single …
process industries, to perform the process of manufacturing. The failure of any single …
Remaining useful life estimation in rolling bearings utilizing data-driven probabilistic E-support vectors regression
We report on a data-driven approach for the remaining useful life (RUL) estimation of rolling
element bearings based on ε-Support Vector Regression (ε-SVR). Lifetime data are …
element bearings based on ε-Support Vector Regression (ε-SVR). Lifetime data are …
Anomaly detection of structural health monitoring data using the maximum likelihood estimation-based Bayesian dynamic linear model
Enormous data are continuously collected by the structural health monitoring system of civil
infrastructures. The structural health monitoring data inevitably involve anomalies caused by …
infrastructures. The structural health monitoring data inevitably involve anomalies caused by …
Online tracking of bearing wear using wavelet packet decomposition and probabilistic modeling: A method for bearing prognostics
Bearings are common and vital elements in rotating machinery. By tracking the condition of
a bearing, unscheduled machinery outages and costly damage caused by a bearing failure …
a bearing, unscheduled machinery outages and costly damage caused by a bearing failure …
Review on prognostics and health management in smart factory: From conventional to deep learning perspectives
At present, the fourth industrial revolution is pushing factories toward an intelligent,
interconnected grid of machinery, communication systems, and computational resources …
interconnected grid of machinery, communication systems, and computational resources …
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 …