A review on vibration-based condition monitoring of rotating machinery
Monitoring vibrations in rotating machinery allows effective diagnostics, as abnormal
functioning states are related to specific patterns that can be extracted from vibration signals …
functioning states are related to specific patterns that can be extracted from vibration signals …
Role of signal processing, modeling and decision making in the diagnosis of rolling element bearing defect: a review
A significant development in condition monitoring techniques has been observed over the
years. The scope of condition monitoring has been shifted from defect identification to its …
years. The scope of condition monitoring has been shifted from defect identification to its …
Structural damage identification using modified Hilbert–Huang transform and support vector machine
Y Diao, D Jia, G Liu, Z Sun, J Xu - Journal of Civil Structural Health …, 2021 - Springer
In the current study, a new structural damage detection algorithm is presented using the
modified Hilbert–Huang transform and support vector machine. The modified Hilbert–Huang …
modified Hilbert–Huang transform and support vector machine. The modified Hilbert–Huang …
[HTML][HTML] Fault diagnosis of bearings based on deep separable convolutional neural network and spatial dropout
J Zhang, K Xiangwei, LI Xueyi, HU Zhiyong… - Chinese Journal of …, 2022 - Elsevier
Bearing pitting, one of the common faults in mechanical systems, is a research hotspot in
both academia and industry. Traditional fault diagnosis methods for bearings are based on …
both academia and industry. Traditional fault diagnosis methods for bearings are based on …
Least square fitting for adaptive wavelet generation and automatic prediction of defect size in the bearing using Levenberg–Marquardt backpropagation
In this communication, an attempt has been made to develop an algorithm for automatic
prediction of the size of the bearing defect during operation of a machine. Features for the …
prediction of the size of the bearing defect during operation of a machine. Features for the …
Rolling bearing fault diagnosis of PSO–LSSVM based on CEEMD entropy fusion
S Gao, T Li, Y Zhang - Transactions of the Canadian Society for …, 2019 - cdnsciencepub.com
Taking aim at the nonstationary nonlinearity of the rolling bearing vibration signal, a rolling
bearing fault diagnosis method based on the entropy fusion feature of complementary …
bearing fault diagnosis method based on the entropy fusion feature of complementary …
The diagnosis approach for rolling bearing fault based on Kurtosis criterion EMD and Hilbert envelope spectrum
C Luo, M Jia, Y Wen - 2017 IEEE 3rd information technology …, 2017 - ieeexplore.ieee.org
A fault diagnosis approach based on empirical mode decomposition (EMD), Hilbert
envelope spectrum and Kurtosis criterion is proposed, by considering the nonlinear and non …
envelope spectrum and Kurtosis criterion is proposed, by considering the nonlinear and non …
Comparison of EMD and EEMD in rolling bearing fault signal analysis
K Fang, H Zhang, H Qi, Y Dai - 2018 IEEE International …, 2018 - ieeexplore.ieee.org
Classical Hilbert-Huang transform (HHT) is commonly used in bearing vibration signal
analysis and fault feature extraction, which consists of two parts: Empirical Mode …
analysis and fault feature extraction, which consists of two parts: Empirical Mode …
[HTML][HTML] Lightweight Network Bearing Intelligent Fault Diagnosis Based on VMD-FK-ShuffleNetV2
W Jiang, Z Qi, A Jiang, S Chang, X Xia - Machines, 2024 - mdpi.com
With the increasing complexity of mechanical equipment and diversification of deep learning
models, vibration signals collected from such equipment are susceptible to noise …
models, vibration signals collected from such equipment are susceptible to noise …
Research progress on bearing fault diagnosis with signal processing methods for rolling element bearings
S Patel, S Patel - Noise & Vibration Worldwide, 2024 - journals.sagepub.com
As a prerequisite for rotating machinery to operate effectively, rolling element bearings play
an essential role. The focus of condition monitoring has initially been on defect identification …
an essential role. The focus of condition monitoring has initially been on defect identification …