Research on sparsity indexes for fault diagnosis of rotating machinery
This paper originated from an investigation of sparsity indexes for fault diagnosis of rotating
machinery. Although various sparsity indexes have been widely applied in machinery fault …
machinery. Although various sparsity indexes have been widely applied in machinery fault …
Investigations on improved Gini indices for bearing fault feature characterization and condition monitoring
Sparsity measures are important and effective tools for accurately characterizing fault
features and degradation trends of rotating machinery. In the past few decades, numerous …
features and degradation trends of rotating machinery. In the past few decades, numerous …
Generalized Gini indices: Complementary sparsity measures to Box-Cox sparsity measures for machine condition monitoring
Sparsity measures that can quantify the sparsity of signals are often used as objective
functions of signal processing and machine learning algorithms (eg, sparse filtering …
functions of signal processing and machine learning algorithms (eg, sparse filtering …
Practical framework of Gini index in the application of machinery fault feature extraction
Gini index (GI) is an outstanding sparsity index that has high robustness for the interference
of the random impulse noise. Yet, as a new index, the definition of GI in different domains is …
of the random impulse noise. Yet, as a new index, the definition of GI in different domains is …
Intelligent fault diagnosis method for rotating machinery via dictionary learning and sparse representation-based classification
Wind power has developed rapidly over the past decade where study on wind turbine fault
diagnosis methods are of great significance. The conventional intelligent diagnosis …
diagnosis methods are of great significance. The conventional intelligent diagnosis …
The automatic selection of an optimal wavelet filter and its enhancement by the new sparsogram for bearing fault detection: Part 2 of the two related manuscripts that …
WT Peter, D Wang - Mechanical Systems and Signal Processing, 2013 - Elsevier
Rolling element bearings are the most important components used in machinery. Bearing
faults, once they have developed, quickly become severe and can result in fatal …
faults, once they have developed, quickly become severe and can result in fatal …
General normalized sparse filtering: A novel unsupervised learning method for rotating machinery fault diagnosis
Z Zhang, S Li, J Wang, Y Xin, Z An - Mechanical Systems and Signal …, 2019 - Elsevier
In the era of data deluge,“big data” generated by mechanical equipment creates higher
requirements for the field of mechanical fault diagnosis. Intelligent diagnosis methods have …
requirements for the field of mechanical fault diagnosis. Intelligent diagnosis methods have …
Nonconvex group sparsity signal decomposition via convex optimization for bearing fault diagnosis
Bearing fault diagnosis is critical for rotating machinery condition monitoring since it is a key
component of rotating machines. One of the challenges for bearing fault diagnosis is to …
component of rotating machines. One of the challenges for bearing fault diagnosis is to …
Sparsity-based algorithm for detecting faults in rotating machines
This paper addresses the detection of periodic transients in vibration signals so as to detect
faults in rotating machines. For this purpose, we present a method to estimate periodic …
faults in rotating machines. For this purpose, we present a method to estimate periodic …
The design of a new sparsogram for fast bearing fault diagnosis: Part 1 of the two related manuscripts that have a joint title as “Two automatic vibration-based fault …
WT Peter, D Wang - Mechanical Systems and Signal Processing, 2013 - Elsevier
Rolling element bearings are widely used in rotating machines. An early warning of bearing
faults helps to prevent machinery breakdown and economic loss. Vibration-based envelope …
faults helps to prevent machinery breakdown and economic loss. Vibration-based envelope …