Language:
English
繁體中文
Help
回圖書館首頁
手機版館藏查詢
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Intelligent reliability and maintain...
~
Li, He.
Linked to FindBook
Google Book
Amazon
博客來
Intelligent reliability and maintainability of energy infrastructure assets
Record Type:
Electronic resources : Monograph/item
Title/Author:
Intelligent reliability and maintainability of energy infrastructure assets/ by He Li ... [et al.].
other author:
Li, He.
Published:
Cham :Springer Nature Switzerland : : 2023.,
Description:
xiii, 148 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:
Advances in Intelligent Reliability and Maintainability of Energy Infrastructure Assets -- Cutting Edge Research Topics on System Safety, Reliability, Maintainability, and Resilience of Energy-critical Infrastructures -- Operation management of critical energy infrastructure: A sustainable approach -- An improved LeNet-5 convolutional neural network supporting condition-based maintenance and fault diagnosis of bearings -- Using Global Average Pooling Convolutional Siamese Networks for fault diagnosis of planetary gearboxes -- Advances in failure prediction of subsea components considering complex dependencies -- An intelligent cost-based consequence model for the offshore system in harsh environments -- A Sustainable Circular Economy in Energy Infrastructure: Application of Supercritical Water Gasification System -- Attention towards Energy infrastructures, Challenges and Solutions.
Contained By:
Springer Nature eBook
Subject:
Electric power systems - Reliability -
Online resource:
https://doi.org/10.1007/978-3-031-29962-9
ISBN:
9783031299629
Intelligent reliability and maintainability of energy infrastructure assets
Intelligent reliability and maintainability of energy infrastructure assets
[electronic resource] /by He Li ... [et al.]. - Cham :Springer Nature Switzerland :2023. - xiii, 148 p. :ill. (some col.), digital ;24 cm. - Studies in systems, decision and control,v. 4732198-4190 ;. - Studies in systems, decision and control ;v. 473..
Advances in Intelligent Reliability and Maintainability of Energy Infrastructure Assets -- Cutting Edge Research Topics on System Safety, Reliability, Maintainability, and Resilience of Energy-critical Infrastructures -- Operation management of critical energy infrastructure: A sustainable approach -- An improved LeNet-5 convolutional neural network supporting condition-based maintenance and fault diagnosis of bearings -- Using Global Average Pooling Convolutional Siamese Networks for fault diagnosis of planetary gearboxes -- Advances in failure prediction of subsea components considering complex dependencies -- An intelligent cost-based consequence model for the offshore system in harsh environments -- A Sustainable Circular Economy in Energy Infrastructure: Application of Supercritical Water Gasification System -- Attention towards Energy infrastructures, Challenges and Solutions.
This book reviews and presents several advanced approaches to energy infrastructure assets' intelligent reliability and maintainability. Each introduced model provides case studies indicating high efficiency, robustness, and applicability, allowing readers to utilize them in their understudy intelligent reliability and maintainability of energy infrastructure assets domains. The book begins by reviewing the state-of-the-art research on the reliability and maintainability of energy infrastructure assets and emphasizes the intelligent tools and methods proposed from a bibliometric and literature review point of view. It then progresses logically, dedicating a chapter to each approach, dynamic Bayesian modeling network, convolutional neural network model, global average pooling-based convolutional Siamese network, an integrated probabilistic model for the failure consequence assessment, and more. This book interests professionals and researchers working in reliability and maintainability and postgraduate and undergraduate students studying intelligent reliability applications and energy infrastructure assets' maintainability.
ISBN: 9783031299629
Standard No.: 10.1007/978-3-031-29962-9doiSubjects--Topical Terms:
3632031
Electric power systems
--Reliability
LC Class. No.: TK1005
Dewey Class. No.: 621.3104
Intelligent reliability and maintainability of energy infrastructure assets
LDR
:03134nmm a2200337 a 4500
001
2317680
003
DE-He213
005
20230503074538.0
006
m d
007
cr nn 008maaau
008
230902s2023 sz s 0 eng d
020
$a
9783031299629
$q
(electronic bk.)
020
$a
9783031299612
$q
(paper)
024
7
$a
10.1007/978-3-031-29962-9
$2
doi
035
$a
978-3-031-29962-9
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
TK1005
072
7
$a
UYQ
$2
bicssc
072
7
$a
TEC009000
$2
bisacsh
072
7
$a
UYQ
$2
thema
082
0 4
$a
621.3104
$2
23
090
$a
TK1005
$b
.I61 2023
245
0 0
$a
Intelligent reliability and maintainability of energy infrastructure assets
$h
[electronic resource] /
$c
by He Li ... [et al.].
260
$a
Cham :
$b
Springer Nature Switzerland :
$b
Imprint: Springer,
$c
2023.
300
$a
xiii, 148 p. :
$b
ill. (some col.), digital ;
$c
24 cm.
490
1
$a
Studies in systems, decision and control,
$x
2198-4190 ;
$v
v. 473
505
0
$a
Advances in Intelligent Reliability and Maintainability of Energy Infrastructure Assets -- Cutting Edge Research Topics on System Safety, Reliability, Maintainability, and Resilience of Energy-critical Infrastructures -- Operation management of critical energy infrastructure: A sustainable approach -- An improved LeNet-5 convolutional neural network supporting condition-based maintenance and fault diagnosis of bearings -- Using Global Average Pooling Convolutional Siamese Networks for fault diagnosis of planetary gearboxes -- Advances in failure prediction of subsea components considering complex dependencies -- An intelligent cost-based consequence model for the offshore system in harsh environments -- A Sustainable Circular Economy in Energy Infrastructure: Application of Supercritical Water Gasification System -- Attention towards Energy infrastructures, Challenges and Solutions.
520
$a
This book reviews and presents several advanced approaches to energy infrastructure assets' intelligent reliability and maintainability. Each introduced model provides case studies indicating high efficiency, robustness, and applicability, allowing readers to utilize them in their understudy intelligent reliability and maintainability of energy infrastructure assets domains. The book begins by reviewing the state-of-the-art research on the reliability and maintainability of energy infrastructure assets and emphasizes the intelligent tools and methods proposed from a bibliometric and literature review point of view. It then progresses logically, dedicating a chapter to each approach, dynamic Bayesian modeling network, convolutional neural network model, global average pooling-based convolutional Siamese network, an integrated probabilistic model for the failure consequence assessment, and more. This book interests professionals and researchers working in reliability and maintainability and postgraduate and undergraduate students studying intelligent reliability applications and energy infrastructure assets' maintainability.
650
0
$a
Electric power systems
$x
Reliability
$x
Data processing.
$3
3632031
650
0
$a
Artificial intelligence
$x
Industrial applications.
$3
653318
650
1 4
$a
Computational Intelligence.
$3
1001631
650
2 4
$a
Industrial and Production Engineering.
$3
891024
700
1
$a
Li, He.
$3
976003
710
2
$a
SpringerLink (Online service)
$3
836513
773
0
$t
Springer Nature eBook
830
0
$a
Studies in systems, decision and control ;
$v
v. 473.
$3
3632030
856
4 0
$u
https://doi.org/10.1007/978-3-031-29962-9
950
$a
Intelligent Technologies and Robotics (SpringerNature-42732)
based on 0 review(s)
Location:
ALL
電子資源
Year:
Volume Number:
Items
1 records • Pages 1 •
1
Inventory Number
Location Name
Item Class
Material type
Call number
Usage Class
Loan Status
No. of reservations
Opac note
Attachments
W9453930
電子資源
11.線上閱覽_V
電子書
EB TK1005
一般使用(Normal)
On shelf
0
1 records • Pages 1 •
1
Multimedia
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login