Machine learning-based fault diagnosis for industrial engineering systems /

"This book provides advanced techniques for precision compensation and fault diagnosis of precision motion systems and rotating machinery. Techniques and applications through experiments and case studies for intelligent precision compensation and fault diagnosis are offered along with the intro...

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Bibliographic Details
Main Authors:	Yang, Rui (Professor of computer engineering) (Author), Zhong, Maiying (Author)
Corporate Author:	Taylor & Francis
Format:	eBook
Language:	English
Published:	Boca Raton ; London : CRC Press, 2022.
Edition:	First edition.
Series:	Advances in intelligent decision-making.
Subjects:	Fault location (Engineering) > Automation. Automatic test equipment. Machinery > Testing. Industrial equipment > Maintenance and repair. Machine learning. Détection de défaut (Ingénierie) > Automatisation. Équipement d'essai automatique. Machines > Essais. Entreprises > Équipement > Entretien et réparations. Apprentissage automatique. Automatic test equipment Industrial equipment > Maintenance and repair Machine learning Machinery > Testing Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Background and related methods
Fault diagnosis method based on recurrent convolutional neural network
Fault diagnosis of rotating machinery gear based on random forest algorithm
Bearing fault diagnosis under different working conditions based on generative adversarial networks
Rotating machinery gearbox fault diagnosis based on one-dimensional convolutional neural network and random forest
Fault diagnosis for rotating machinery gearbox based on improved random forest algorithm
Imbalanced data fault diagnosis based on hybrid feature dimensionality reduction and varied density based safe level synthetic minority oversampling technique.