Wavelets for fault diagnosis of rotary machines: A review with applications
Over the last 20 years, particularly in last 10 years, great progress has been made in the
theory and applications of wavelets and many publications have been seen in the field of …
theory and applications of wavelets and many publications have been seen in the field of …
The entropy algorithm and its variants in the fault diagnosis of rotating machinery: A review
Rotating machines have been widely used in industrial engineering. The fault diagnosis of
rotating machines plays a vital important role to reduce the catastrophic failures and heavy …
rotating machines plays a vital important role to reduce the catastrophic failures and heavy …
Reliable fault diagnosis for low-speed bearings using individually trained support vector machines with kernel discriminative feature analysis
M Kang, J Kim, JM Kim, ACC Tan… - IEEE Transactions on …, 2014 - ieeexplore.ieee.org
This paper proposes a highly reliable fault diagnosis approach for low-speed bearings. The
proposed approach first extracts wavelet-based fault features that represent diverse …
proposed approach first extracts wavelet-based fault features that represent diverse …
Prediction of compressive strength and portland cement composition using cross-validation and feature ranking techniques
Prediction of compressive strength and concrete composition using machine learning
models is an essential feature in civil engineering applications. In the present paper, a …
models is an essential feature in civil engineering applications. In the present paper, a …
Feature extraction and fault severity classification in ball bearings
The present study attempts to diagnose severity of faults in ball bearings using various
machine learning techniques, like support vector machine (SVM) and artificial neural …
machine learning techniques, like support vector machine (SVM) and artificial neural …
An improved VMD with empirical mode decomposition and its application in incipient fault detection of rolling bearing
F Jiang, Z Zhu, W Li - IEEE Access, 2018 - ieeexplore.ieee.org
Transient impulse analysis is an effective way to detect the bearing fault at its early stage.
However, it is hard to precisely extract these so-called transient impulses because these …
However, it is hard to precisely extract these so-called transient impulses because these …
Comparison of two classifiers; K‐nearest neighbor and artificial neural network, for fault diagnosis on a main engine journal‐bearing
Vibration analysis is an accepted method in condition monitoring of machines, since it can
provide useful and reliable information about machine working condition. This paper …
provide useful and reliable information about machine working condition. This paper …
A multiscale permutation entropy based approach to select wavelet for fault diagnosis of ball bearings
The detection and diagnosis of bearing health status using vibration signal has been an
important subject for extensive research over the past few decades. The objective of this …
important subject for extensive research over the past few decades. The objective of this …
Bearing fault diagnosis based on multi-scale permutation entropy and adaptive neuro fuzzy classifier
The rolling element bearing is among the most frequently encountered component in a
rotating machine. Bearing fault can cause machinery breakdown and lead to productivity …
rotating machine. Bearing fault can cause machinery breakdown and lead to productivity …
Reliable fault diagnosis for incipient low-speed bearings using fault feature analysis based on a binary bat algorithm
M Kang, J Kim, JM Kim - Information Sciences, 2015 - Elsevier
In this paper, we propose a highly reliable fault diagnosis scheme for incipient low-speed
rolling element bearing failures. The scheme consists of fault feature calculation …
rolling element bearing failures. The scheme consists of fault feature calculation …