A novel local linear embedding algorithm via local mutual representation for bearing fault diagnosis

The locally linear embedding algorithm (LLE) mainly extracts significant features by mining the local neighborhood structure of the data. However, when the data exhibit strong nonlinearity in high-dimensional space, the single neighborhood structure of the LLE algorithm may not accurately capture th...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Reliability engineering & system safety Jg. 247; S. 110135
Hauptverfasser: Liu, Yuanhong, Shi, Baoxin, Lu, Shixiang, Gao, Zhi-Wei, Zhang, Fangfang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.07.2024
Schlagworte:
ISSN:0951-8320, 1879-0836
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Abstract The locally linear embedding algorithm (LLE) mainly extracts significant features by mining the local neighborhood structure of the data. However, when the data exhibit strong nonlinearity in high-dimensional space, the single neighborhood structure of the LLE algorithm may not accurately capture the local linear relationships between instances, which degrades the performances of the LLE. Therefore, we propose a multi-structure neighborhood locally linear embedding algorithm via local mutual representation (LMR-LLE). Firstly, in each neighborhood, multiple local neighborhood structures of one instance are mined via local mutual representation to enhance the interconnectivity between the instances. Furthermore, the multiple neighborhood structures are fused in the low-dimensional space to construct a global reconstruction model, and the ultimate significant features are acquired by determining the model’s optimal solution. Finally, the extracted features are fed into a classifier for bearing fault diagnosis. Extensive experiments on two rolling bearing datasets illustrate that the LMR-LLE based diagnosis method has better performance accuracy than conventional LLE-based algorithms. •A multi-structure neighborhood locally linear embedding algorithm is proposed using local mutual representation.•Features extracted are fed into a classifier for bearing fault diagnosis.•Intensive experiments are implemented on two rolling bearing datasets to demonstrate the performance of the algorithm.
AbstractList The locally linear embedding algorithm (LLE) mainly extracts significant features by mining the local neighborhood structure of the data. However, when the data exhibit strong nonlinearity in high-dimensional space, the single neighborhood structure of the LLE algorithm may not accurately capture the local linear relationships between instances, which degrades the performances of the LLE. Therefore, we propose a multi-structure neighborhood locally linear embedding algorithm via local mutual representation (LMR-LLE). Firstly, in each neighborhood, multiple local neighborhood structures of one instance are mined via local mutual representation to enhance the interconnectivity between the instances. Furthermore, the multiple neighborhood structures are fused in the low-dimensional space to construct a global reconstruction model, and the ultimate significant features are acquired by determining the model’s optimal solution. Finally, the extracted features are fed into a classifier for bearing fault diagnosis. Extensive experiments on two rolling bearing datasets illustrate that the LMR-LLE based diagnosis method has better performance accuracy than conventional LLE-based algorithms. •A multi-structure neighborhood locally linear embedding algorithm is proposed using local mutual representation.•Features extracted are fed into a classifier for bearing fault diagnosis.•Intensive experiments are implemented on two rolling bearing datasets to demonstrate the performance of the algorithm.
ArticleNumber 110135
Author Lu, Shixiang
Zhang, Fangfang
Liu, Yuanhong
Gao, Zhi-Wei
Shi, Baoxin
Author_xml – sequence: 1
  givenname: Yuanhong
  surname: Liu
  fullname: Liu, Yuanhong
  email: liuyuanhong@nepu.edu.cn
  organization: Research Centre for Digitalization and Intelligent Diagnosis to New Energies, College of Electrical and Information Engineering, Northeast Petroleum University, Daqing 163318, China
– sequence: 2
  givenname: Baoxin
  surname: Shi
  fullname: Shi, Baoxin
  email: 15546696560@163.com
  organization: Research Centre for Digitalization and Intelligent Diagnosis to New Energies, College of Electrical and Information Engineering, Northeast Petroleum University, Daqing 163318, China
– sequence: 3
  givenname: Shixiang
  surname: Lu
  fullname: Lu, Shixiang
  email: lsx94@nepu.edu.cn
  organization: Research Centre for Digitalization and Intelligent Diagnosis to New Energies, College of Electrical and Information Engineering, Northeast Petroleum University, Daqing 163318, China
– sequence: 4
  givenname: Zhi-Wei
  orcidid: 0009-0008-3453-6707
  surname: Gao
  fullname: Gao, Zhi-Wei
  email: Gaozhiwei@nepu.edu.cn
  organization: Research Centre for Digitalization and Intelligent Diagnosis to New Energies, College of Electrical and Information Engineering, Northeast Petroleum University, Daqing 163318, China
– sequence: 5
  givenname: Fangfang
  surname: Zhang
  fullname: Zhang, Fangfang
  email: zhff4u@qlu.edu.cn
  organization: Department of Electronics, Electricity and Control, Qilu University of Technology, Shandong 250353, China
BookMark eNp9kMlqwzAQQEVJoUnaH-hJP2B3ZHmFXkLoBoFe2rPQMk4VbClITqB_Xxvn1EMuMzDMm-WtyMJ5h4Q8MkgZsPLpkAaMMc0gy1M2VnhxQ5asrpoEal4uyBKagiU1z-COrGI8AEDeFNWSmA11_owd7byWY7QOZaDYKzTGuj2V3d4HO_z09Gzlpak_DacxBTyOS9ENcrDe0dYHqkZ4olp56gZqrNw7H228J7et7CI-XPKafL--fG3fk93n28d2s0s0BxgSZXKla65UUSlVSSiYlqVUEnOArFIZYy3jtQKORQbAuWpNU9agpMKG5arga1LPc3XwMQZshbbzdUOQthMMxGRLHMRkS0y2xGxrRLN_6DHYXobf69DzDOH41NliEFFbdBqNDagHYby9hv8B8reIBg
CitedBy_id crossref_primary_10_1088_1361_6501_adead1
crossref_primary_10_1016_j_isatra_2025_05_044
crossref_primary_10_1016_j_neucom_2025_129900
crossref_primary_10_1016_j_ress_2024_110362
crossref_primary_10_1016_j_measurement_2024_116466
crossref_primary_10_1016_j_patcog_2025_111938
crossref_primary_10_1016_j_rineng_2025_106789
Cites_doi 10.1016/j.ymssp.2019.106587
10.1016/j.ress.2022.108986
10.1109/TCYB.2021.3086193
10.1016/j.proeng.2017.01.138
10.1126/science.290.5500.2323
10.1038/s41551-022-00914-1
10.1109/TIM.2022.3219307
10.1016/j.ress.2022.108353
10.1016/j.measurement.2021.110239
10.1016/j.ymssp.2015.06.006
10.1080/00461520.2021.1939700
10.1007/s40009-017-0536-7
10.1016/j.ress.2021.108208
10.1007/s11277-011-0416-2
10.1109/JIOT.2022.3141382
10.1016/j.patcog.2021.108336
10.1016/j.eswa.2010.07.119
10.1016/j.ress.2023.109096
10.1016/j.procs.2017.05.171
10.1109/ACCESS.2023.3304700
10.1016/j.renene.2022.11.064
10.1109/TNNLS.2023.3290974
10.1016/j.neucom.2020.11.048
10.1016/j.ress.2021.107813
10.1016/j.ress.2022.108648
10.1109/TII.2022.3190034
10.1002/mp.16235
ContentType Journal Article
Copyright 2024
Copyright_xml – notice: 2024
DBID AAYXX
CITATION
DOI 10.1016/j.ress.2024.110135
DatabaseName CrossRef
DatabaseTitle CrossRef
DatabaseTitleList
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EISSN 1879-0836
ExternalDocumentID 10_1016_j_ress_2024_110135
S0951832024002096
GroupedDBID --K
--M
.~1
0R~
123
1B1
1~.
1~5
29P
4.4
457
4G.
5VS
7-5
71M
8P~
9JN
9JO
AABNK
AACTN
AAEDT
AAEDW
AAFJI
AAIAV
AAIKJ
AAKOC
AALRI
AAOAW
AAQFI
AAQXK
AAXUO
ABEFU
ABFNM
ABJNI
ABMAC
ABMMH
ABTAH
ABXDB
ACDAQ
ACGFS
ACIWK
ACNNM
ACRLP
ADBBV
ADEZE
ADMUD
ADTZH
AEBSH
AECPX
AEKER
AENEX
AFKWA
AFRAH
AFTJW
AGHFR
AGUBO
AGYEJ
AHHHB
AHJVU
AIEXJ
AIKHN
AITUG
AJOXV
AKRWK
AKYCK
ALMA_UNASSIGNED_HOLDINGS
AMFUW
AMRAJ
AOMHK
ASPBG
AVARZ
AVWKF
AXJTR
AZFZN
BJAXD
BKOJK
BLXMC
CS3
DU5
EBS
EFJIC
EJD
EO8
EO9
EP2
EP3
FDB
FEDTE
FGOYB
FIRID
FNPLU
FYGXN
G-2
G-Q
GBLVA
HVGLF
HZ~
IHE
J1W
JJJVA
KOM
LY7
M41
MO0
N9A
O-L
O9-
OAUVE
OZT
P-8
P-9
P2P
PC.
PRBVW
Q38
R2-
RIG
ROL
RPZ
SDF
SDG
SES
SET
SEW
SPC
SPCBC
SSB
SSO
SST
SSZ
T5K
TN5
WUQ
XPP
ZMT
ZY4
~G-
9DU
AATTM
AAXKI
AAYWO
AAYXX
ABWVN
ACLOT
ACRPL
ACVFH
ADCNI
ADNMO
AEIPS
AEUPX
AFJKZ
AFPUW
AGQPQ
AIGII
AIIUN
AKBMS
AKYEP
ANKPU
APXCP
CITATION
EFKBS
EFLBG
~HD
ID FETCH-LOGICAL-c300t-bd4bc83bb57bb7a051ca6abae40027b211f138b03e520033bfd9680babe914b53
ISICitedReferencesCount 8
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001244023400001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 0951-8320
IngestDate Sat Nov 29 01:50:07 EST 2025
Tue Nov 18 21:46:24 EST 2025
Sat May 25 15:40:37 EDT 2024
IsPeerReviewed true
IsScholarly true
Keywords Bearing fault diagnosis
Feature extraction
Locally linear embedding algorithm
Local mutual representation
Language English
LinkModel OpenURL
MergedId FETCHMERGED-LOGICAL-c300t-bd4bc83bb57bb7a051ca6abae40027b211f138b03e520033bfd9680babe914b53
ORCID 0009-0008-3453-6707
ParticipantIDs crossref_citationtrail_10_1016_j_ress_2024_110135
crossref_primary_10_1016_j_ress_2024_110135
elsevier_sciencedirect_doi_10_1016_j_ress_2024_110135
PublicationCentury 2000
PublicationDate July 2024
2024-07-00
PublicationDateYYYYMMDD 2024-07-01
PublicationDate_xml – month: 07
  year: 2024
  text: July 2024
PublicationDecade 2020
PublicationTitle Reliability engineering & system safety
PublicationYear 2024
Publisher Elsevier Ltd
Publisher_xml – name: Elsevier Ltd
References Lei, Yang, Jiang, Jia, Li, Nandi (b3) 2020; 138
Krishnan, Rajpurkar, Topol (b21) 2022; 6
Chen, Luo, Huang, Jiang, Kaynak (b13) 2024; 35
Roweis, Saul (b16) 2000; 290
Jin, Zuo, Wang, Cui, Li (b9) 2021; 52
Liu, He, Liu, Qu (b22) 2021; 186
Liu, He, Liu, Qu (b29) 2021; 186
Mövik, Bäck, Pettersson (b18) 2023; 50
Song, Liu, Han, Zeng, Yu, Zheng (b10) 2022; 10
Costa, Sánchez (b15) 2022; 222
Zhang, Li, Tian, Jiang, Luo, Yin (b7) 2023; 231
Zeng, Yang, Zheng, Cheng (b32) 2016; 66
Wu, Jing, Wang (b23) 2020; 24
Zhang, Zhang, An, Luo, Yin (b4) 2023
Chen, Liu, Alippi, Huang, Liu (b14) 2022
Cao, Ding, Jia, Tian (b11) 2021; 215
Zhong, Chen, Jiang, Ren (b19) 2022; 122
Mehta, Tyagi, Rao, Kumar, Chauhan (b24) 2017; 40
Lu, Gao, Xu, Jiang, Zhang, Wang (b1) 2022; 18
Liu, Hu, Zhang (b30) 2021; 428
Jain, Tapaswi, Shukla (b28) 2012; 67
Tabandeh, Sharma, Gardoni (b6) 2022; 219
Han, Li (b12) 2022; 226
Xie, Xu, Jiang, Lu, Wang (b5) 2023; 202
Liu, Li, Wang, Chen, Chen, Qiu (b26) 2022; 71
Ziegelmeier, Kirby, Peterson (b25) 2017; 108
Zhiwei, Cecati, Ding (b2) 2015
Ye, Tang, Zhu, Yang, Li, Hao (b20) 2022; 60
Zhang, Li, Tian, Luo, Yin (b8) 2023; 233
Zhao, Wang, Hua, Liu, Zhang, Hu (b27) 2017; 174
Song, Liao, Jia, Kong, Niu (b33) 2023; 11
Simonsmeier, Flaig, Deiglmayr, Schalk, Schneider (b17) 2022; 57
Kankar, Sharma, Harsha (b31) 2011; 38
Lu (10.1016/j.ress.2024.110135_b1) 2022; 18
Song (10.1016/j.ress.2024.110135_b10) 2022; 10
Liu (10.1016/j.ress.2024.110135_b29) 2021; 186
Liu (10.1016/j.ress.2024.110135_b22) 2021; 186
Han (10.1016/j.ress.2024.110135_b12) 2022; 226
Zhang (10.1016/j.ress.2024.110135_b4) 2023
Cao (10.1016/j.ress.2024.110135_b11) 2021; 215
Chen (10.1016/j.ress.2024.110135_b14) 2022
Zhao (10.1016/j.ress.2024.110135_b27) 2017; 174
Zeng (10.1016/j.ress.2024.110135_b32) 2016; 66
Zhang (10.1016/j.ress.2024.110135_b7) 2023; 231
Simonsmeier (10.1016/j.ress.2024.110135_b17) 2022; 57
Jin (10.1016/j.ress.2024.110135_b9) 2021; 52
Liu (10.1016/j.ress.2024.110135_b30) 2021; 428
Chen (10.1016/j.ress.2024.110135_b13) 2024; 35
Ye (10.1016/j.ress.2024.110135_b20) 2022; 60
Jain (10.1016/j.ress.2024.110135_b28) 2012; 67
Mövik (10.1016/j.ress.2024.110135_b18) 2023; 50
Zhang (10.1016/j.ress.2024.110135_b8) 2023; 233
Ziegelmeier (10.1016/j.ress.2024.110135_b25) 2017; 108
Zhiwei (10.1016/j.ress.2024.110135_b2) 2015
Krishnan (10.1016/j.ress.2024.110135_b21) 2022; 6
Wu (10.1016/j.ress.2024.110135_b23) 2020; 24
Lei (10.1016/j.ress.2024.110135_b3) 2020; 138
Tabandeh (10.1016/j.ress.2024.110135_b6) 2022; 219
Roweis (10.1016/j.ress.2024.110135_b16) 2000; 290
Kankar (10.1016/j.ress.2024.110135_b31) 2011; 38
Zhong (10.1016/j.ress.2024.110135_b19) 2022; 122
Song (10.1016/j.ress.2024.110135_b33) 2023; 11
Xie (10.1016/j.ress.2024.110135_b5) 2023; 202
Mehta (10.1016/j.ress.2024.110135_b24) 2017; 40
Costa (10.1016/j.ress.2024.110135_b15) 2022; 222
Liu (10.1016/j.ress.2024.110135_b26) 2022; 71
References_xml – volume: 24
  start-page: 323
  year: 2020
  end-page: 330
  ident: b23
  article-title: Improved weighted local linear embedding algorithm based on Laplacian eigenmaps
  publication-title: Int J Knowl-Based Intell Eng Syst
– volume: 10
  start-page: 3037
  year: 2022
  end-page: 3046
  ident: b10
  article-title: Edge-intelligence-based condition monitoring of beam pumping units under heavy noise in industrial internet of things for industry 4.0
  publication-title: IEEE Internet Things J
– volume: 186
  year: 2021
  ident: b22
  article-title: Local linear embedding algorithm of mutual neighborhood based on multi-information fusion metric
  publication-title: Measurement
– volume: 122
  year: 2022
  ident: b19
  article-title: A cascade reconstruction model with generalization ability evaluation for anomaly detection in videos
  publication-title: Pattern Recognit
– volume: 67
  start-page: 879
  year: 2012
  end-page: 893
  ident: b28
  article-title: Location estimation based on semi-supervised locally linear embedding (SSLLE) approach for indoor wireless networks
  publication-title: Wirel Pers Commun
– volume: 233
  year: 2023
  ident: b8
  article-title: An integrated multi-head dual sparse self-attention network for remaining useful life prediction
  publication-title: Reliab Eng Syst Saf
– start-page: 1
  year: 2023
  end-page: 12
  ident: b4
  article-title: An integrated multitasking intelligent bearing fault diagnosis scheme based on representation learning under imbalanced sample condition
  publication-title: IEEE Trans Neural Netw Learn Syst
– volume: 226
  year: 2022
  ident: b12
  article-title: Out-of-distribution detection-assisted trustworthy machinery fault diagnosis approach with uncertainty-aware deep ensembles
  publication-title: Reliab Eng Syst Saf
– volume: 202
  start-page: 143
  year: 2023
  end-page: 153
  ident: b5
  article-title: The fault frequency priors fusion deep learning framework with application to fault diagnosis of offshore wind turbines
  publication-title: Renew Energy
– volume: 186
  year: 2021
  ident: b29
  article-title: Local linear embedding algorithm of mutual neighborhood based on multi-information fusion metric
  publication-title: Measurement
– volume: 108
  start-page: 635
  year: 2017
  end-page: 644
  ident: b25
  article-title: Sparse locally linear embedding
  publication-title: Procedia Comput Sci
– volume: 6
  start-page: 1346
  year: 2022
  end-page: 1352
  ident: b21
  article-title: Self-supervised learning in medicine and healthcare
  publication-title: Nat Biomed Eng
– volume: 174
  start-page: 281
  year: 2017
  end-page: 288
  ident: b27
  article-title: Recognition of control chart pattern using improved supervised locally linear embedding and support vector machine
  publication-title: Procedia Eng
– volume: 66
  start-page: 533
  year: 2016
  end-page: 545
  ident: b32
  article-title: Maximum margin classification based on flexible convex hulls for fault diagnosis of roller bearings
  publication-title: Mech Syst Signal Process
– volume: 290
  start-page: 2323
  year: 2000
  end-page: 2326
  ident: b16
  article-title: Nonlinear dimensionality reduction by locally linear embedding
  publication-title: Science
– volume: 52
  start-page: 12687
  year: 2021
  end-page: 12697
  ident: b9
  article-title: An integrated model-based and data-driven gap metric method for fault detection and isolation
  publication-title: IEEE Trans Cybern
– volume: 57
  start-page: 31
  year: 2022
  end-page: 54
  ident: b17
  article-title: Domain-specific prior knowledge and learning: A meta-analysis
  publication-title: Educ Psychol
– volume: 40
  start-page: 189
  year: 2017
  end-page: 196
  ident: b24
  article-title: Modified locally linear embedding with affine transformation
  publication-title: Nat Acad Sci Lett
– volume: 215
  year: 2021
  ident: b11
  article-title: A novel temporal convolutional network with residual self-attention mechanism for remaining useful life prediction of rolling bearings
  publication-title: Reliab Eng Syst Saf
– volume: 219
  year: 2022
  ident: b6
  article-title: Uncertainty propagation in risk and resilience analysis of hierarchical systems
  publication-title: Reliab Eng Syst Saf
– volume: 11
  start-page: 86686
  year: 2023
  end-page: 86696
  ident: b33
  article-title: Rolling bearing fault diagnosis under different severity based on statistics detection index and canonical discriminant analysis
  publication-title: IEEE Access
– year: 2015
  ident: b2
  article-title: A survey of fault diagnosis and fault-tolerant techniques—Part II: Fault diagnosis with knowledge-based and hybrid/active approaches
  publication-title: IEEE Trans Ind Electron
– volume: 35
  start-page: 2969
  year: 2024
  end-page: 2983
  ident: b13
  article-title: Transfer learning-motivated intelligent fault diagnosis designs: A survey, insights, and perspectives
  publication-title: IEEE Trans Neural Netw Learn Syst
– volume: 50
  start-page: 1879
  year: 2023
  end-page: 1892
  ident: b18
  article-title: Impact of delineation errors on the estimated organ at risk dose and of dose errors on the normal tissue complication probability model
  publication-title: Med Phys
– volume: 60
  start-page: 1
  year: 2022
  end-page: 15
  ident: b20
  article-title: A multiscale framework with unsupervised learning for remote sensing image registration
  publication-title: IEEE Trans Geosci Remote Sens
– volume: 138
  year: 2020
  ident: b3
  article-title: Applications of machine learning to machine fault diagnosis: A review and roadmap
  publication-title: Mech Syst Signal Process
– volume: 231
  year: 2023
  ident: b7
  article-title: A variational local weighted deep sub-domain adaptation network for remaining useful life prediction facing cross-domain condition
  publication-title: Reliab Eng Syst Saf
– start-page: 1
  year: 2022
  end-page: 14
  ident: b14
  article-title: Explainable intelligent fault diagnosis for nonlinear dynamic systems: From unsupervised to supervised learning
  publication-title: IEEE Trans Neural Netw Learn Syst
– volume: 18
  start-page: 9101
  year: 2022
  end-page: 9111
  ident: b1
  article-title: Class-imbalance privacy-preserving federated learning for decentralized fault diagnosis with biometric authentication
  publication-title: IEEE Trans Ind Inf
– volume: 222
  year: 2022
  ident: b15
  article-title: Variational encoding approach for interpretable assessment of remaining useful life estimation
  publication-title: Reliab Eng Syst Saf
– volume: 71
  start-page: 1
  year: 2022
  end-page: 4
  ident: b26
  article-title: Hessian locally linear embedding of PMU data for efficient fault detection in power systems
  publication-title: IEEE Trans Instrum Meas
– volume: 428
  start-page: 280
  year: 2021
  end-page: 290
  ident: b30
  article-title: Bearing feature extraction using multi-structure locally linear embedding
  publication-title: Neurocomputing
– volume: 38
  start-page: 1876
  year: 2011
  end-page: 1886
  ident: b31
  article-title: Fault diagnosis of ball bearings using machine learning methods
  publication-title: Expert Syst Appl
– volume: 138
  year: 2020
  ident: 10.1016/j.ress.2024.110135_b3
  article-title: Applications of machine learning to machine fault diagnosis: A review and roadmap
  publication-title: Mech Syst Signal Process
  doi: 10.1016/j.ymssp.2019.106587
– volume: 231
  year: 2023
  ident: 10.1016/j.ress.2024.110135_b7
  article-title: A variational local weighted deep sub-domain adaptation network for remaining useful life prediction facing cross-domain condition
  publication-title: Reliab Eng Syst Saf
  doi: 10.1016/j.ress.2022.108986
– volume: 52
  start-page: 12687
  issue: 12
  year: 2021
  ident: 10.1016/j.ress.2024.110135_b9
  article-title: An integrated model-based and data-driven gap metric method for fault detection and isolation
  publication-title: IEEE Trans Cybern
  doi: 10.1109/TCYB.2021.3086193
– volume: 174
  start-page: 281
  year: 2017
  ident: 10.1016/j.ress.2024.110135_b27
  article-title: Recognition of control chart pattern using improved supervised locally linear embedding and support vector machine
  publication-title: Procedia Eng
  doi: 10.1016/j.proeng.2017.01.138
– volume: 290
  start-page: 2323
  issue: 5500
  year: 2000
  ident: 10.1016/j.ress.2024.110135_b16
  article-title: Nonlinear dimensionality reduction by locally linear embedding
  publication-title: Science
  doi: 10.1126/science.290.5500.2323
– volume: 6
  start-page: 1346
  issue: 12
  year: 2022
  ident: 10.1016/j.ress.2024.110135_b21
  article-title: Self-supervised learning in medicine and healthcare
  publication-title: Nat Biomed Eng
  doi: 10.1038/s41551-022-00914-1
– volume: 71
  start-page: 1
  year: 2022
  ident: 10.1016/j.ress.2024.110135_b26
  article-title: Hessian locally linear embedding of PMU data for efficient fault detection in power systems
  publication-title: IEEE Trans Instrum Meas
  doi: 10.1109/TIM.2022.3219307
– volume: 222
  year: 2022
  ident: 10.1016/j.ress.2024.110135_b15
  article-title: Variational encoding approach for interpretable assessment of remaining useful life estimation
  publication-title: Reliab Eng Syst Saf
  doi: 10.1016/j.ress.2022.108353
– volume: 186
  year: 2021
  ident: 10.1016/j.ress.2024.110135_b29
  article-title: Local linear embedding algorithm of mutual neighborhood based on multi-information fusion metric
  publication-title: Measurement
  doi: 10.1016/j.measurement.2021.110239
– volume: 66
  start-page: 533
  year: 2016
  ident: 10.1016/j.ress.2024.110135_b32
  article-title: Maximum margin classification based on flexible convex hulls for fault diagnosis of roller bearings
  publication-title: Mech Syst Signal Process
  doi: 10.1016/j.ymssp.2015.06.006
– volume: 57
  start-page: 31
  issue: 1
  year: 2022
  ident: 10.1016/j.ress.2024.110135_b17
  article-title: Domain-specific prior knowledge and learning: A meta-analysis
  publication-title: Educ Psychol
  doi: 10.1080/00461520.2021.1939700
– volume: 40
  start-page: 189
  year: 2017
  ident: 10.1016/j.ress.2024.110135_b24
  article-title: Modified locally linear embedding with affine transformation
  publication-title: Nat Acad Sci Lett
  doi: 10.1007/s40009-017-0536-7
– volume: 219
  year: 2022
  ident: 10.1016/j.ress.2024.110135_b6
  article-title: Uncertainty propagation in risk and resilience analysis of hierarchical systems
  publication-title: Reliab Eng Syst Saf
  doi: 10.1016/j.ress.2021.108208
– year: 2015
  ident: 10.1016/j.ress.2024.110135_b2
  article-title: A survey of fault diagnosis and fault-tolerant techniques—Part II: Fault diagnosis with knowledge-based and hybrid/active approaches
  publication-title: IEEE Trans Ind Electron
– volume: 67
  start-page: 879
  year: 2012
  ident: 10.1016/j.ress.2024.110135_b28
  article-title: Location estimation based on semi-supervised locally linear embedding (SSLLE) approach for indoor wireless networks
  publication-title: Wirel Pers Commun
  doi: 10.1007/s11277-011-0416-2
– volume: 10
  start-page: 3037
  issue: 4
  year: 2022
  ident: 10.1016/j.ress.2024.110135_b10
  article-title: Edge-intelligence-based condition monitoring of beam pumping units under heavy noise in industrial internet of things for industry 4.0
  publication-title: IEEE Internet Things J
  doi: 10.1109/JIOT.2022.3141382
– volume: 122
  year: 2022
  ident: 10.1016/j.ress.2024.110135_b19
  article-title: A cascade reconstruction model with generalization ability evaluation for anomaly detection in videos
  publication-title: Pattern Recognit
  doi: 10.1016/j.patcog.2021.108336
– volume: 38
  start-page: 1876
  issue: 3
  year: 2011
  ident: 10.1016/j.ress.2024.110135_b31
  article-title: Fault diagnosis of ball bearings using machine learning methods
  publication-title: Expert Syst Appl
  doi: 10.1016/j.eswa.2010.07.119
– volume: 233
  year: 2023
  ident: 10.1016/j.ress.2024.110135_b8
  article-title: An integrated multi-head dual sparse self-attention network for remaining useful life prediction
  publication-title: Reliab Eng Syst Saf
  doi: 10.1016/j.ress.2023.109096
– volume: 108
  start-page: 635
  year: 2017
  ident: 10.1016/j.ress.2024.110135_b25
  article-title: Sparse locally linear embedding
  publication-title: Procedia Comput Sci
  doi: 10.1016/j.procs.2017.05.171
– volume: 11
  start-page: 86686
  year: 2023
  ident: 10.1016/j.ress.2024.110135_b33
  article-title: Rolling bearing fault diagnosis under different severity based on statistics detection index and canonical discriminant analysis
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2023.3304700
– volume: 186
  year: 2021
  ident: 10.1016/j.ress.2024.110135_b22
  article-title: Local linear embedding algorithm of mutual neighborhood based on multi-information fusion metric
  publication-title: Measurement
  doi: 10.1016/j.measurement.2021.110239
– start-page: 1
  year: 2022
  ident: 10.1016/j.ress.2024.110135_b14
  article-title: Explainable intelligent fault diagnosis for nonlinear dynamic systems: From unsupervised to supervised learning
  publication-title: IEEE Trans Neural Netw Learn Syst
– volume: 202
  start-page: 143
  year: 2023
  ident: 10.1016/j.ress.2024.110135_b5
  article-title: The fault frequency priors fusion deep learning framework with application to fault diagnosis of offshore wind turbines
  publication-title: Renew Energy
  doi: 10.1016/j.renene.2022.11.064
– volume: 35
  start-page: 2969
  issue: 3
  year: 2024
  ident: 10.1016/j.ress.2024.110135_b13
  article-title: Transfer learning-motivated intelligent fault diagnosis designs: A survey, insights, and perspectives
  publication-title: IEEE Trans Neural Netw Learn Syst
  doi: 10.1109/TNNLS.2023.3290974
– volume: 60
  start-page: 1
  year: 2022
  ident: 10.1016/j.ress.2024.110135_b20
  article-title: A multiscale framework with unsupervised learning for remote sensing image registration
  publication-title: IEEE Trans Geosci Remote Sens
– volume: 428
  start-page: 280
  year: 2021
  ident: 10.1016/j.ress.2024.110135_b30
  article-title: Bearing feature extraction using multi-structure locally linear embedding
  publication-title: Neurocomputing
  doi: 10.1016/j.neucom.2020.11.048
– volume: 215
  year: 2021
  ident: 10.1016/j.ress.2024.110135_b11
  article-title: A novel temporal convolutional network with residual self-attention mechanism for remaining useful life prediction of rolling bearings
  publication-title: Reliab Eng Syst Saf
  doi: 10.1016/j.ress.2021.107813
– start-page: 1
  year: 2023
  ident: 10.1016/j.ress.2024.110135_b4
  article-title: An integrated multitasking intelligent bearing fault diagnosis scheme based on representation learning under imbalanced sample condition
  publication-title: IEEE Trans Neural Netw Learn Syst
– volume: 226
  year: 2022
  ident: 10.1016/j.ress.2024.110135_b12
  article-title: Out-of-distribution detection-assisted trustworthy machinery fault diagnosis approach with uncertainty-aware deep ensembles
  publication-title: Reliab Eng Syst Saf
  doi: 10.1016/j.ress.2022.108648
– volume: 18
  start-page: 9101
  issue: 12
  year: 2022
  ident: 10.1016/j.ress.2024.110135_b1
  article-title: Class-imbalance privacy-preserving federated learning for decentralized fault diagnosis with biometric authentication
  publication-title: IEEE Trans Ind Inf
  doi: 10.1109/TII.2022.3190034
– volume: 24
  start-page: 323
  issue: 4
  year: 2020
  ident: 10.1016/j.ress.2024.110135_b23
  article-title: Improved weighted local linear embedding algorithm based on Laplacian eigenmaps
  publication-title: Int J Knowl-Based Intell Eng Syst
– volume: 50
  start-page: 1879
  issue: 3
  year: 2023
  ident: 10.1016/j.ress.2024.110135_b18
  article-title: Impact of delineation errors on the estimated organ at risk dose and of dose errors on the normal tissue complication probability model
  publication-title: Med Phys
  doi: 10.1002/mp.16235
SSID ssj0004957
Score 2.467748
Snippet The locally linear embedding algorithm (LLE) mainly extracts significant features by mining the local neighborhood structure of the data. However, when the...
SourceID crossref
elsevier
SourceType Enrichment Source
Index Database
Publisher
StartPage 110135
SubjectTerms Bearing fault diagnosis
Feature extraction
Local mutual representation
Locally linear embedding algorithm
Title A novel local linear embedding algorithm via local mutual representation for bearing fault diagnosis
URI https://dx.doi.org/10.1016/j.ress.2024.110135
Volume 247
WOSCitedRecordID wos001244023400001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVESC
  databaseName: Elsevier SD Freedom Collection Journals 2021
  customDbUrl:
  eissn: 1879-0836
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0004957
  issn: 0951-8320
  databaseCode: AIEXJ
  dateStart: 19950101
  isFulltext: true
  titleUrlDefault: https://www.sciencedirect.com
  providerName: Elsevier
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9NAEF6FlgMcEE_RUtAeuFmu_Lb3GKFS4FAhUUTExdqx18SVY1eJHaU_oP-7sw8_KKgCJC5W5Oxmo51P45nxN98S8hYwa4iDPLc5yzBBYQX6wSAUNi84BrNMADB92ER8dpYsFuzzbHbd98Jsq7iuk92OXf5XU-M9NLZsnf0Lcw8_ijfwMxodr2h2vP6R4edW3WxFZamnlCWjSL62xApErvpXePWjWZftcmVtS24GrTrVRaIELvtmJE1ABJysuJa8q1pZqJW8vHIzDWklqVmLfV9ZYlQ3VJjSOtHWhhdGbkRxf8pOOf6O18vGPDiVSGSpX4A0u3LkCamh-NUOYTwMPeWqwPt9WdrfRDktXHjBQHI11bS-o2akL-mypGujl9HvaoR2yknMlIr21Gt7WqjzlyeALkZcHMtixbFcVjY6uFoS5Zay9he5mFxL8mg9zOXukX0vDhn69_35x5PFp7HBlmnJ2P7Pme4rTRS8vdLvI5xJ1HL-mDwy6Qada5g8ITNRPyUPJyKUz0g-pwowVGGBasDQATB0AAxFwJhBGjD0Z8BQBAw1gKEKMHQAzHPy9f3J-bsPtjl7w858x2ltyAPIEh8gjAFijq474xEHLuRWxeC5buH6CTi-kLpdvg9FzqLEAQ6CuQGE_guyVze1eEloFBYix0QOM_MkyDOPY0QZuREkPHbAZ84Bcfv9SjMjTC_PR6nSnoF4kco9TuUep3qPD4g1zLnUsix3jg57M6QmsNQBY4qouWPe4T_Oe0UejIA_InvtuhOvyf1s25ab9RsDrhuhfqA4
linkProvider Elsevier
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+novel+local+linear+embedding+algorithm+via+local+mutual+representation+for+bearing+fault+diagnosis&rft.jtitle=Reliability+engineering+%26+system+safety&rft.au=Liu%2C+Yuanhong&rft.au=Shi%2C+Baoxin&rft.au=Lu%2C+Shixiang&rft.au=Gao%2C+Zhi-Wei&rft.date=2024-07-01&rft.pub=Elsevier+Ltd&rft.issn=0951-8320&rft.eissn=1879-0836&rft.volume=247&rft_id=info:doi/10.1016%2Fj.ress.2024.110135&rft.externalDocID=S0951832024002096
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0951-8320&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0951-8320&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0951-8320&client=summon