View in EDS

A reasoning approach-based pattern graph for analyzing the risk level of correlations among catenary components considering time distribution.

Saved in:
Bibliographic Details
Title: A reasoning approach-based pattern graph for analyzing the risk level of correlations among catenary components considering time distribution.
Authors: Diyang, Liu1 (AUTHOR), Shibin, Gao1 (AUTHOR), Jiaming, Luo1 (AUTHOR), Xiaoguang, Wei1 (AUTHOR) wei_xiaoguang@126.com, Jian, Shi2 (AUTHOR)
Source: Reliability Engineering & System Safety. May2024, Vol. 245, pN.PAG-N.PAG. 1p.
Subjects: Power resources, Databases, Couplings (Gearing), Certainty, Railroads
Abstract: • We define two types of fault correlations based on the time intervals among faulty components: simultaneous fault correlations and sequential fault correlations to investigate the fault propagation characteristics among faulty components at different time scales • The MYCIN method is introduced to construct the belief and disbelief models by defining the residual belief of fault correlations to evaluate the risk levels of fault correlations. • Simultaneous/sequential risk pattern graphs are proposed by linking and identifying virtual paths using explicit fault correlations to make reasonable inferences for inexplicit correlations that are included in the dataset but are hidden and thus not directly observable. The catenary system is a crucial part of the traction power supply system, consisting of multiple components interconnected through mechanical coupling. To reveal the risk characteristics of fault propagation between catenary components, this paper presents a reasoning approach-based pattern graph for analyzing the risk level of correlations of components considering time distribution from a statistical perspective. Initially, we define simultaneous fault correlations and sequential fault correlations among faulty components based on the different time distributions to capture the risk propagation features among components. Then, the MYCIN model is introduced to construct a certainty factor considering the belief and disbelief of fault correlations to calculate the risk levels of simultaneous/sequential fault correlations. Finally, we develop a risk pattern graph by linking the virtual paths to assess the risk level of inexplicit correlations hidden within the historical dataset. Simulation results, conducted based on the fault database of the Chengdu Railway Bureau, show the proposed method can effectively assess the risk level of correlations among faulty components to reveal the fault propagation features, which provides valuable references for proactive maintenance. [ABSTRACT FROM AUTHOR]
Copyright of Reliability Engineering & System Safety is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 175873276
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: A reasoning approach-based pattern graph for analyzing the risk level of correlations among catenary components considering time distribution.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Diyang%2C+Liu%22">Diyang, Liu</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Shibin%2C+Gao%22">Shibin, Gao</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jiaming%2C+Luo%22">Jiaming, Luo</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xiaoguang%2C+Wei%22">Xiaoguang, Wei</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> wei_xiaoguang@126.com</i><br /><searchLink fieldCode="AR" term="%22Jian%2C+Shi%22">Jian, Shi</searchLink><relatesTo>2</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Reliability+Engineering+%26+System+Safety%22">Reliability Engineering & System Safety</searchLink>. May2024, Vol. 245, pN.PAG-N.PAG. 1p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Power+resources%22">Power resources</searchLink><br /><searchLink fieldCode="DE" term="%22Databases%22">Databases</searchLink><br /><searchLink fieldCode="DE" term="%22Couplings+%28Gearing%29%22">Couplings (Gearing)</searchLink><br /><searchLink fieldCode="DE" term="%22Certainty%22">Certainty</searchLink><br /><searchLink fieldCode="DE" term="%22Railroads%22">Railroads</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: • We define two types of fault correlations based on the time intervals among faulty components: simultaneous fault correlations and sequential fault correlations to investigate the fault propagation characteristics among faulty components at different time scales • The MYCIN method is introduced to construct the belief and disbelief models by defining the residual belief of fault correlations to evaluate the risk levels of fault correlations. • Simultaneous/sequential risk pattern graphs are proposed by linking and identifying virtual paths using explicit fault correlations to make reasonable inferences for inexplicit correlations that are included in the dataset but are hidden and thus not directly observable. The catenary system is a crucial part of the traction power supply system, consisting of multiple components interconnected through mechanical coupling. To reveal the risk characteristics of fault propagation between catenary components, this paper presents a reasoning approach-based pattern graph for analyzing the risk level of correlations of components considering time distribution from a statistical perspective. Initially, we define simultaneous fault correlations and sequential fault correlations among faulty components based on the different time distributions to capture the risk propagation features among components. Then, the MYCIN model is introduced to construct a certainty factor considering the belief and disbelief of fault correlations to calculate the risk levels of simultaneous/sequential fault correlations. Finally, we develop a risk pattern graph by linking the virtual paths to assess the risk level of inexplicit correlations hidden within the historical dataset. Simulation results, conducted based on the fault database of the Chengdu Railway Bureau, show the proposed method can effectively assess the risk level of correlations among faulty components to reveal the fault propagation features, which provides valuable references for proactive maintenance. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Reliability Engineering & System Safety is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=175873276
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.ress.2024.110035
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 1
        StartPage: N.PAG
    Subjects:
      – SubjectFull: Power resources
        Type: general
      – SubjectFull: Databases
        Type: general
      – SubjectFull: Couplings (Gearing)
        Type: general
      – SubjectFull: Certainty
        Type: general
      – SubjectFull: Railroads
        Type: general
    Titles:
      – TitleFull: A reasoning approach-based pattern graph for analyzing the risk level of correlations among catenary components considering time distribution.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Diyang, Liu
      – PersonEntity:
          Name:
            NameFull: Shibin, Gao
      – PersonEntity:
          Name:
            NameFull: Jiaming, Luo
      – PersonEntity:
          Name:
            NameFull: Xiaoguang, Wei
      – PersonEntity:
          Name:
            NameFull: Jian, Shi
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 05
              Text: May2024
              Type: published
              Y: 2024
          Identifiers:
            – Type: issn-print
              Value: 09518320
          Numbering:
            – Type: volume
              Value: 245
          Titles:
            – TitleFull: Reliability Engineering & System Safety
              Type: main
ResultId 1