Data-driven fault diagnosis for traction systems in high-speed trains: A survey, challenges, and perspectives
Recently, to ensure the reliability and safety of high-speed trains, detection and diagnosis of
faults (FDD) in traction systems have become an active issue in the transportation area over …
faults (FDD) in traction systems have become an active issue in the transportation area over …
Transfer learning-motivated intelligent fault diagnosis designs: A survey, insights, and perspectives
Over the last decade, transfer learning has attracted a great deal of attention as a new
learning paradigm, based on which fault diagnosis (FD) approaches have been intensively …
learning paradigm, based on which fault diagnosis (FD) approaches have been intensively …
Some current directions in the theory and application of statistical process monitoring
WH Woodall, DC Montgomery - Journal of Quality Technology, 2014 - Taylor & Francis
The purpose of this paper is to provide an overview and our perspective of recent research
and applications of statistical process monitoring. The focus is on work done over the past …
and applications of statistical process monitoring. The focus is on work done over the past …
Distribution-free multivariate process control based on log-linear modeling
P Qiu - IIE Transactions, 2008 - Taylor & Francis
This paper considers Statistical Process Control (SPC) when the process measurement is
multivariate. In the literature, most existing multivariate SPC procedures assume that the in …
multivariate. In the literature, most existing multivariate SPC procedures assume that the in …
Monitoring multivariate process variability for individual observations
L Huwang, AB Yeh, CW Wu - Journal of Quality technology, 2007 - Taylor & Francis
Most of the existing control charts for monitoring multivariate process variability are based on
subgroup sizes greater than one. In many practical applications, however, only individual …
subgroup sizes greater than one. In many practical applications, however, only individual …
Monitoring the ratio of two normal variables using run rules type control charts
Recent studies show that Shewhart-type control charts monitoring the ratio of two normal
random variables are useful to perform continuous surveillance in several manufacturing …
random variables are useful to perform continuous surveillance in several manufacturing …
Stochastic deep Koopman model for quality propagation analysis in multistage manufacturing systems
The modeling of multistage manufacturing systems (MMSs) has attracted increased attention
from both academia and industry. Recent advancements in deep learning methods provide …
from both academia and industry. Recent advancements in deep learning methods provide …
Control charts for monitoring linear profiles with within‐profile correlation using Gaussian process models
Y Zhang, Z He, C Zhang… - Quality and Reliability …, 2014 - Wiley Online Library
Profile monitoring is the utilization of control charts for checking the stability of the quality of a
product over time when the product quality is characterized by a function at each time point …
product over time when the product quality is characterized by a function at each time point …
Phase-I monitoring of high-dimensional covariance matrix using an adaptive thresholding LASSO rule
High-dimensional variability monitoring and diagnosing is of great prominence for the
quality improvement and cost reduction. Most of the existing control charts are mainly based …
quality improvement and cost reduction. Most of the existing control charts are mainly based …
Nonparametric multivariate covariance chart for monitoring individual observations
Parametric and nonparametric multivariate control charts that are proven very useful in
monitoring the covariance matrix of multivariate normally or “nearly” normally distributed …
monitoring the covariance matrix of multivariate normally or “nearly” normally distributed …