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Related Concept Videos

Ferromagnetism01:31

Ferromagnetism

Materials like iron, nickel, and cobalt consist of magnetic domains, within which the magnetic dipoles are arranged parallel to each other. The magnetic dipoles are rigidly aligned in the same direction within a domain by quantum mechanical coupling among the atoms. This coupling is so strong that even thermal agitation at room temperature cannot break it. The result is that each domain has a net dipole moment. However, some materials have weaker coupling, and are ferromagnetic at lower...
Torque On A Current Loop In A Magnetic Field01:13

Torque On A Current Loop In A Magnetic Field

The most common application of magnetic force on current-carrying wires is in electric motors. These consist of loops of wire, which are placed between the magnets with a magnetic field. When current flows through the loops, the magnetic field applies torque, which causes the shaft to rotate, thus converting electrical energy to mechanical energy.
Consider a rectangular current-carrying loop containing N turns of wire, placed in a uniform magnetic field. The net force on a current-carrying loop...
Magnetic Field Of A Current Loop01:16

Magnetic Field Of A Current Loop

Consider a circular loop with a radius a, that carries a current I. The magnetic field due to the current at an arbitrary point P along the axis of the loop can be calculated using the Biot-Savart law.
Magnetic Field of a Solenoid01:18

Magnetic Field of a Solenoid

A solenoid is a conducting wire coated with an insulating material, wound tightly in the form of a helical coil. The magnetic field due to a solenoid is the vector sum of the magnetic fields due to its individual turns. Therefore, for an ideal solenoid, the magnetic field within the solenoid is directly proportional to the number of turns per unit length and the current. Conversely, the magnetic field outside the solenoid is zero.
Consider a solenoid with 100 turns wrapped around a cylinder of...
Magnetic Susceptibility and Permeability01:31

Magnetic Susceptibility and Permeability

In linear magnetic materials, like paramagnets and diamagnets, magnetization is proportional to the magnetic field intensity. The constant of proportionality, a dimensionless number, is called magnetic susceptibility. The value of the susceptibility depends on the type of material.
When diamagnetic materials are placed under an external magnetic field, the moments opposite to the field are induced. Hence, the susceptibility for diamagnets has a minimal negative value of 10-5–10-6. Since...
Magnetism01:30

Magnetism

Magnets are commonly found in everyday objects, such as toys, hangers, elevators, doorbells, and computer devices. Experimentation on these magnets shows that all magnets have two poles: one is labeled north (N) and the other south (S). Magnetic poles repel if they are alike and attract if unlike. Moreover, both poles of a magnet attract unmagnetized pieces of iron.
An individual magnetic pole cannot be isolated. No matter how small, every piece of a magnet contains a north pole and a south...

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Related Experiment Video

Updated: May 14, 2026

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

Demagnetization Severity Detection in Permanent Magnet Synchronous Motors Based on Temperature Signal and

Zhiqiang Wang1, Shihao Yan1, Haodong Sun1

  • 1School of Electrical Engineering, Tiangong University, Tianjin 300387, China.

Sensors (Basel, Switzerland)
|May 13, 2026
PubMed
Summary

This study introduces a new method to detect demagnetization severity in permanent magnet synchronous motors (PMSMs) using temperature signals and a Conditionally Modulated Multi-Scale Convolutional Neural Network (CMSCNN). The approach achieves high accuracy in both simulations and real-world tests.

Keywords:
Convolutional Neural Networkdemagnetization severity detectionlocal demagnetizationpermanent magnet synchronous motortemperature

Related Experiment Videos

Last Updated: May 14, 2026

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

Area of Science:

  • Electrical Engineering
  • Machine Learning
  • Motor Diagnostics

Background:

  • Detecting demagnetization severity in permanent magnet synchronous motors (PMSMs) is challenging.
  • Existing methods may struggle with accuracy and real-time application.

Purpose of the Study:

  • To propose an effective method for detecting demagnetization severity in PMSMs.
  • To leverage temperature signals and advanced neural networks for improved diagnostics.

Main Methods:

  • Electromagnetic analysis of stator current harmonics using Fast Fourier Transform (FFT).
  • Development of an electromagnetic-thermal coupling model to simulate winding temperatures.
  • Implementation of a Conditionally Modulated Multi-Scale Convolutional Neural Network (CMSCNN) for feature learning.

Main Results:

  • The proposed CMSCNN method achieved 98.06% average accuracy on simulation data.
  • The method demonstrated 93.34% average accuracy on experimental data from a faulty prototype.
  • The approach outperformed a baseline Convolutional Neural Network (CNN) model.

Conclusions:

  • The proposed temperature-signal-based CMSCNN method is effective for demagnetization severity detection in PMSMs.
  • This technique offers a reliable solution for motor health monitoring and fault diagnosis.
  • The study validates the practical applicability of the developed diagnostic approach.