Detection of bearing faults in mechanical systems using stator current monitoring

S Singh, N Kumar - IEEE Transactions on Industrial Informatics, 2016 - ieeexplore.ieee.org
Induction motors have been responsible for running mechanical systems in the industry for
many decades. Their diagnosis still remains a hot quest for the researchers using various …

Tool wear predictive model based on least squares support vector machines

D Shi, NN Gindy - Mechanical systems and signal processing, 2007 - Elsevier
The development of tool wear monitoring system for machining processes has been well
recognised in industry due to the ever-increased demand for product quality and productivity …

OrbitNet: A new CNN model for automatic fault diagnostics of turbomachines

X Jiang, S Yang, F Wang, S Xu, X Wang… - Applied Soft Computing, 2021 - Elsevier
Unplanned outage due to faults in a high-fidelity turbomachine such as steam turbine and
centrifugal compressor often results in the reduced reliability and productivity of a factory …

Rotating machinery diagnostics using deep learning on orbit plot images

H Jeong, S Park, S Woo, S Lee - Procedia Manufacturing, 2016 - Elsevier
Although the orbit analysis (orbit shape and size) is commonly used to diagnose rotating
machinery, the diagnosis heavily depends on the expert knowledge or experience due to …

Dynamic behaviours of a full floating ring bearing supported turbocharger rotor with engine excitation

L Tian, WJ Wang, ZJ Peng - Journal of Sound and Vibration, 2011 - Elsevier
The rotor dynamic behaviour of turbochargers (TC) has been paid significant attention
because of its importance in their healthy operation. Commonly, the TC is firmly mounted on …

Multi-branch convolutional neural network with generalized shaft orbit for fault diagnosis of active magnetic bearing-rotor system

X Yan, C Zhang, Y Liu - Measurement, 2021 - Elsevier
Fault diagnosis based on vibration signals in active magnetic bearing-rotor systems is an
important research topic. However, it is difficult to obtain discriminative features to represent …

Rotor unbalance fault diagnosis using DBN based on multi-source heterogeneous information fusion

J Yan, Y Hu, C Guo - Procedia Manufacturing, 2019 - Elsevier
In the age of Internet of Things and Industrial 4.0, new advanced methods need to be
proposed to analyse massive multi-source heterogeneous data from rotating machinery …

An orbit-based encoder–forecaster deep learning method for condition monitoring of large turbomachines

X Jiang, Z Wang, Q Chen, X Cheng, S Xu… - Expert Systems with …, 2024 - Elsevier
Most data-driven methods used in condition monitoring and early faults alarming of large
turbomachines need to manually extract features for modeling, which inevitably introduces …

Empirical mode decomposition, an adaptive approach for interpreting shaft vibratory signals of large rotating machinery

W Yang, PJ Tavner - Journal of Sound and Vibration, 2009 - Elsevier
The Fourier transform (FT) has been the most popular method for analyzing large rotating
machine shaft vibration problems, but it assumes that these vibration signals are linear and …

Sensorless speed measurement of induction motor using Hilbert transform and interpolated fast Fourier transform

D Shi, PJ Unsworth, RX Gao - IEEE Transactions on …, 2006 - ieeexplore.ieee.org
A new scheme based on the Hilbert transform and the interpolated fast Fourier transform
(IFFT) is proposed to improve the estimation accuracy of induction motor speed from motor …