Related references
Note: Only part of the references are listed.Enhancement of time-frequency post-processing readability for nonstationary signal analysis of rotating machinery: Principle and validation
Dong Zhang et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2022)
Motor Fault Diagnosis Using Image Visual Information and Bag of Words Model
Zhuo Long et al.
IEEE SENSORS JOURNAL (2021)
Fault diagnosis of rolling bearing based on empirical mode decomposition and improved manhattan distance in symmetrized dot pattern image
Yongjian Sun et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2021)
A Novel Advancing Signal Processing Method Based on Coupled Multi-Stable Stochastic Resonance for Fault Detection
Hongjiang Cui et al.
APPLIED SCIENCES-BASEL (2021)
Bearing Fault Classification Using Ensemble Empirical Mode Decomposition and Convolutional Neural Network
Rafia Nishat Toma et al.
ELECTRONICS (2021)
Induction Motor Bearing Fault Classification Using Extreme Learning Machine Based on Power Features
Niloy Sikder et al.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING (2021)
Diagnosis of Rotor Asymmetries Faults in Induction Machines Using the Rectified Stator Current
Ruben Puche-Panadero et al.
IEEE TRANSACTIONS ON ENERGY CONVERSION (2020)
A Concentrated Time-Frequency Analysis Tool for Bearing Fault Diagnosis
Gang Yu
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2020)
Temporal envelope detection by the square root of the three-phase currents for IM rotor fault diagnosis
Hamid Khelfi et al.
ELECTRICAL ENGINEERING (2020)
A New Intelligent Bearing Fault Diagnosis Method Using SDP Representation and SE-CNN
Hui Wang et al.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2020)
Signal based condition monitoring techniques for fault detection and diagnosis of induction motors: A state-of-the-art review
Purushottam Gangsar et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2020)
Generative adversarial networks for data augmentation in machine fault diagnosis
Siyu Shao et al.
COMPUTERS IN INDUSTRY (2019)
An Approach on MCSA-Based Fault Detection Using Independent Component Analysis and Neural Networks
Juan Enrique Garcia-Bracamonte et al.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2019)
Evaluation of Current Signature in Bearing Defects by Envelope Analysis of the vibration in induction motors
Isac Antonio dos Santos Areias et al.
ENERGIES (2019)
Modulation Sideband Separation Using the Teager-Kaiser Energy Operator for Rotor Fault Diagnostics of Induction Motors
Haiyang Li et al.
ENERGIES (2019)
The reflection of evolving bearing faults in the stator current's extended park vector approach for induction machines
Bram Corne et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2018)
Novel approach using Hilbert Transform for multiple broken rotor bars fault location detection for three phase induction motor
Mina B. Abd-el-Malek et al.
ISA TRANSACTIONS (2018)
Infrared thermography based diagnosis of inter-turn fault and cooling system failure in three phase induction motor
Gurmeet Singh et al.
INFRARED PHYSICS & TECHNOLOGY (2017)
Methodology for fault detection in induction motors via sound and vibration signals
Paulo Antonio Delgado-Arredondo et al.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2017)
Electric Motor Fault Detection and Diagnosis by Kernel Density Estimation and Kullback-Leibler Divergence Based on Stator Current Measurements
Andrea Giantomassi et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2015)
Models for bearing damage detection in induction motors using stator current monitoring
Martin Bloedt et al.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2008)
A frequency-domain detection of stator winding faults in induction machines using an external flux sensor
H Henao et al.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS (2003)