Skip to main navigation Skip to search Skip to main content

Leveraging Machine Learning for Pipeline Condition Assessment

  • Hongfang Lu
  • , Zhao Dong Xu
  • , Xulei Zang
  • , Dongmin Xi
  • , Tom Iseley
  • , John C. Matthews
  • , Niannian Wang
  • Southeast University
  • Purdue University
  • Louisiana Tech University
  • Zhengzhou University

Research output: Contribution to journalArticlepeer-review

Original languageEnglish
Article number04023024
JournalJournal of Pipeline Systems Engineering and Practice
Volume14
Issue number3
DOIs
StatePublished - Aug 1 2023
Externally publishedYes

ASJC Scopus Subject Areas

  • Civil and Structural Engineering
  • Mechanical Engineering

Keywords

  • Fault diagnosis
  • Machine learning
  • Pipeline condition assessment
  • Risk prediction
  • Visual defect recognition

Fingerprint

Dive into the research topics of 'Leveraging Machine Learning for Pipeline Condition Assessment'. Together they form a unique fingerprint.

Cite this