New Generation Artificial Intelligence-Driven Diagnosis and Maintenance Techniques (Registro nro. 276553)

MARC details
000 -LIDER
fixed length control field 05662nam a22006135i 4500
001 - CONTROL NUMBER
control field 978-981-97-1176-5
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250516160144.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 240928s2024 si | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789819711765
-- 978-981-97-1176-5
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q342
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM004000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Wen, Guangrui.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
245 10 - TITLE STATEMENT
Title New Generation Artificial Intelligence-Driven Diagnosis and Maintenance Techniques
Medium [electronic resource] :
Remainder of title Advanced Machine Learning Models, Methods and Applications /
Statement of responsibility, etc. by Guangrui Wen, Zihao Lei, Xuefeng Chen, Xin Huang.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2024.
264 #1 -
-- Singapore :
-- Springer Nature Singapore :
-- Imprint: Springer,
-- 2024.
300 ## - PHYSICAL DESCRIPTION
Extent XVII, 349 p. 190 illus., 182 illus. in color.
Other physical details online resource.
336 ## -
-- text
-- txt
-- rdacontent
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-- computer
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-- rdamedia
338 ## -
-- online resource
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-- rdacarrier
347 ## -
-- text file
-- PDF
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490 1# - SERIES STATEMENT
Series statement Smart Sensors, Measurement and Instrumentation,
International Standard Serial Number 2194-8410 ;
Volume/sequential designation 46
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Introduction -- Overview of Intelligent Fault Diagnosis and Maintenance for Rotating Machinery -- Deep Learning and Sparse Representation Coupled Intelligent Diagnosis and Maintenance -- Sparse Model-Driven Deep Learning for Weak Fault Diagnosis of Rolling Bearings -- Memory Residual Regression Autoencoder for Bearing Fault Detection -- Transfer Learning-based Intelligent Diagnosis and Maintenance -- Fault Diagnosis of Polytropic Conditions Based on Transfer Learning -- Performance Degradation Assessment Based on Transfer learning for Bearing -- Remaining Useful Life Prediction on -- Transfer Learning for Bearing -- Adversarial Learning-based Intelligent Diagnosis and Maintenance -- Deep Sequence Multi-distribution Adversarial Model for Abnormal Condition Detection in Industry -- Multi-Scale Lightweight Fault Diagnosis Model Based on Adversarial Learning -- Performance Degradation Assessment Based on Adversarial Learning for Bearing -- Graph-structured Information-based Intelligent Diagnosisand Maintenance -- Modelling and Feature Extraction Method Based on Complex Network and Its Application in Machine Fault Diagnosis -- Community Clustering Algorithms and Its Application in Machine Fault Diagnosis -- Remaining Life Assessment of Rolling Bearing Based on Graph Neural Network -- Multi-source Information Fusion-based Intelligent Diagnosis and Maintenance -- Intelligent Fault Diagnosis Method Based on Multi-source Data and Multi-Feature Fusion -- D-S Evidence Theory and Its Application for Fault Diagnosis of Machinery -- Conclusion, Challenges, and Future Work -- Conclusion, Challenges, and Future Work.
520 ## - SUMMARY, ETC.
Summary, etc. The intelligent diagnosis and maintenance of the machine mainly includes condition monitoring, fault diagnosis, performance degradation assessment and remaining useful life prediction, which plays an important role in protecting people's lives and property. In actual engineering scenarios, machine users always hope to use an automatic method to shorten the maintenance cycle and improve the accuracy of fault diagnosis and prognosis. In the past decade, Artificial Intelligence applications have flourished in many different fields, which also provide powerful tools for intelligent diagnosis and maintenance. This book highlights the latest advances and trends in new generation artificial intelligence-driven techniques, including knowledge-driven deep learning, transfer learning, adversarial learning, complex network, graph neural network and multi-source information fusion, for diagnosis and maintenance of rotating machinery. Its primary focus is on the utilization of advanced artificial intelligence techniques to monitor, diagnose, and perform predictive maintenance of critical structures and machines, such as aero-engine, gas turbines, wind turbines, and machine tools. The main markets of this book include academic and industrial fields, such as academic institutions, libraries of university, industrial research center. This book is essential reading for faculty members of university, graduate students, and industry professionals in the fields of diagnosis and maintenance.
541 ## - IMMEDIATE SOURCE OF ACQUISITION NOTE
Owner UABC ;
Method of acquisition Perpetuidad
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Computational intelligence.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Manufactures.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Security systems.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Computational Intelligence.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Artificial Intelligence.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Machines, Tools, Processes.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Término temático o nombre geográfico como elemento de entrada Security Science and Technology.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Lei, Zihao.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Chen, Xuefeng.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Huang, Xin.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9789819711758
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9789819711772
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Relationship information Printed edition:
International Standard Book Number 9789819711789
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Smart Sensors, Measurement and Instrumentation,
-- 2194-8410 ;
Volume number/sequential designation 46
856 40 - ELECTRONIC LOCATION AND ACCESS
Public note Libro electrónico
Uniform Resource Identifier http://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-981-97-1176-5
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912 ## -
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942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Libro Electrónico
Existencias
Estado de retiro Colección Ubicación permanente Ubicación actual Fecha de ingreso Total Checkouts Date last seen Número de copia Tipo de material
  Colección de Libros Electrónicos Biblioteca Electrónica Biblioteca Electrónica 16/05/2025   16/05/2025 1 Libro Electrónico

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