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Early Detection of Faults in Induction Motors

In modern industries, induction motors are the backbone of numerous applications, powering everything from manufacturing facilities to transportation systems. While they are known for their reliability, unexpected failures can still occur, leading to increased operational costs, facility damage, or...

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Bibliographic Details
Main Author: Morinigo-Sotelo, Daniel
Other Authors: Romero-Troncoso, Rene, Pons-Llinares, Joan
Format: eBook
Language:English
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
Subjects:
Fault Severity
Machine Learning
Supervised Learning
Phasor Compensation
Shorted Turn Faults
Condition Monitoring
Measurement Techniques
Back Emf
Induction Motors
Ac Machines
Current Signal Analysis
Electric Machine
Feedforward Compensation
Deep Learning
Signal Analysis
Apfft
History Of Engineering And Technology / Bicssc
Dynamic Information Fusion
Induction Machines
Physical Variables
Fault Detection
Multiple Coupled Circuit Model
Technology: General Issues / Bicssc
Data-driven
Traction Motor
Power Connection Failures
Parameter Identification
Early Damage Detection
Frequency Analysis
Prony Method
Induction Motor
Early Detection
Fault Diagnosis
Signal Processing
Unlabeled Learning
Fault-tolerant Control
Fast Fourier Transform
Svm
Rotating Machines
Incipient Fault
Time-frequency Decompositions
Artificial Intelligence
Broken Rotor Bar
Fault Classification
Spectral Analysis
Itsc Fault
Bearing Diagnosis
Negative Sequence Currents
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
Description
Summary:In modern industries, induction motors are the backbone of numerous applications, powering everything from manufacturing facilities to transportation systems. While they are known for their reliability, unexpected failures can still occur, leading to increased operational costs, facility damage, or service interruptions. "Early Detection and Fault Diagnosis of Induction Motors" is a comprehensive volume that compiles ten innovative journal articles focused on maintaining these machines. The papers explore a variety of techniques that introduce new ideas to the field.
Item Description:Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
Physical Description:1 electronic resource (200 p.)
ISBN:9783036593357
9783036593340
books978-3-0365-9334-0

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