Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Electro-mechanical Systems01:19

Electro-mechanical Systems

946
Electromechanical systems are intricate configurations that effectively combine electrical and mechanical elements to achieve a desired outcome. Central to many of these systems is the DC motor, a device that converts electrical energy into mechanical motion, enabling various applications ranging from simple fans to complex robotic mechanisms.
A key component of the DC motor is the armature, a rotating circuit positioned within a magnetic field. As an electric current passes through the...
946
Power System Three-Phase Short Circuits01:21

Power System Three-Phase Short Circuits

83
Determining the subtransient fault current in a power system involves representing transformers by their leakage reactances, transmission lines by their equivalent series reactances, and synchronous machines as constant voltage sources behind their subtransient reactances. In this analysis, certain elements are excluded, such as winding resistances, series resistances, shunt admittances, delta-Y phase shifts, armature resistance, saturation, saliency, non-rotating impedance loads, and small...
83

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Lightweight Statistical and Texture Feature Approach for Breast Thermogram Analysis.

Journal of imaging·2025
Same author

A High-Performance and Cost-Effective Field Programmable Gate Array-Based Motor Drive Emulator.

Micromachines·2023
Same author

Modeling of Particulate Pollutants Using a Memory-Based Recurrent Neural Network Implemented on an FPGA.

Micromachines·2023
Same author

Broken Bar Fault Detection Using Taylor-Fourier Filters and Statistical Analysis.

Entropy (Basel, Switzerland)·2023
Same author

Single-Pixel Near-Infrared 3D Image Reconstruction in Outdoor Conditions.

Micromachines·2022
Same author

ECG-Based Identification of Sudden Cardiac Death through Sparse Representations.

Sensors (Basel, Switzerland)·2021
Same journal

Research on a Regional Availability Evaluation Model for Road-Area High-Entropy Energy Based on Synergy Factors.

Entropy (Basel, Switzerland)·2026
Same journal

Atmospheric Turbulence Channel Modeling and Performance Analysis of a CO-ZP-OFDM Coherent Optical Communication System for UAV Air-to-Ground Scenarios.

Entropy (Basel, Switzerland)·2026
Same journal

Information Geometry and Asymptotic Theory for SMML Estimators.

Entropy (Basel, Switzerland)·2026
Same journal

Correlation Entropy and Power-Law Kinetics.

Entropy (Basel, Switzerland)·2026
Same journal

Research on the Contagion of Systemic Financial Risk Under the Impact of Climate Risks-From the Perspective of Complex Networks and Machine Learning.

Entropy (Basel, Switzerland)·2026
Same journal

The Statistical-Mechanical Meaning of the Wave Function of Quantum Mechanics.

Entropy (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Jun 27, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

1.6K

Entropy-Based Methods for Motor Fault Detection: A Review.

Sarahi Aguayo-Tapia1, Gerardo Avalos-Almazan1, Jose de Jesus Rangel-Magdaleno1

  • 1Digital Systems Group, National Institute of Astrophysics, Optics and Electronics, Puebla 72840, Mexico.

Entropy (Basel, Switzerland)
|April 26, 2024
PubMed
Summary
This summary is machine-generated.

Entropy analysis helps detect motor faults by measuring signal disorder. This method is crucial for industrial machinery integrity, preventing damage and operational downtime.

Keywords:
artificial-intelligence-based classifiersentropyfeature vectorsmotor fault detection

More Related Videos

A Method for Evaluating Timeliness and Accuracy of Volitional Motor Responses to Vibrotactile Stimuli
07:28

A Method for Evaluating Timeliness and Accuracy of Volitional Motor Responses to Vibrotactile Stimuli

Published on: August 2, 2016

7.2K
A Novel Single Animal Motor Function Tracking System Using Simple, Readily Available Software
08:22

A Novel Single Animal Motor Function Tracking System Using Simple, Readily Available Software

Published on: August 31, 2018

6.6K

Related Experiment Videos

Last Updated: Jun 27, 2025

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
06:45

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

1.6K
A Method for Evaluating Timeliness and Accuracy of Volitional Motor Responses to Vibrotactile Stimuli
07:28

A Method for Evaluating Timeliness and Accuracy of Volitional Motor Responses to Vibrotactile Stimuli

Published on: August 2, 2016

7.2K
A Novel Single Animal Motor Function Tracking System Using Simple, Readily Available Software
08:22

A Novel Single Animal Motor Function Tracking System Using Simple, Readily Available Software

Published on: August 31, 2018

6.6K

Area of Science:

  • Signal Processing
  • Machine Learning
  • Industrial Monitoring

Background:

  • Entropy quantifies signal complexity, useful for anomaly detection in various systems.
  • Early motor fault detection is vital in industrial settings to prevent damage and ensure operational continuity.

Purpose of the Study:

  • To explore entropy-based methodologies for motor fault detection.
  • To bridge theoretical entropy concepts with practical industrial needs.
  • To review recent advancements in entropy for motor fault diagnosis.

Main Methods:

  • Assessing signal complexity (vibrations, stator currents) using entropy measures.
  • Generating feature vectors from complex signal characteristics.
  • Utilizing artificial intelligence classifiers for fault identification.

Main Results:

  • Entropy methods effectively characterize motor signals for fault detection.
  • Recent literature shows significant progress in entropy-based fault diagnosis over the past decade.
  • The approach aids in distinguishing between healthy and faulty motor operational states.

Conclusions:

  • Entropy theory provides a robust framework for motor fault detection in industrial applications.
  • Integrating entropy-based signal analysis enhances machinery integrity and predictive maintenance.
  • This research contributes to advancements in signal processing, AI, and industrial control systems.