Visualization of damage progress on solid oxide fuel cell

Ken Ichi Fukui, Shogo Akasaki, Kazuhisa Sato, Junichiro Mizusaki, Koichi Moriyama, Satoshi Kurihara, Masayuki Numao

Research output: Contribution to journalArticlepeer-review


Fuel cell is regarded as a highly efficient power generation system as well as low-pollution. In particular, SOFC (Solid Oxide Fuel Cell) has high generation efficiency. However, a crucial issue in putting SOFC into practical use is the establishment of a technique for evaluating the deterioration. We have previously developed a technique to measure the mechanical damage of SOFC using Acoustic Emission (AE) method. This paper applied the kernel Self-Organizing Map (SOM), which is an extended neural network model, to AE data observed from damage progress on SOFC to produce a cluster map reflecting similarity of AE waves. The obtained map visualized the change of occurrence patterns of similar AE waves showing four phases of damage progress. The interpretation of the result as physical phenomenon is limited at this stage, though our methodology provides a common foundation for comprehensive damage evaluation system as well as monitoring.

Original languageEnglish
Pages (from-to)223-232
Number of pages10
JournalNihon Kikai Gakkai Ronbunshu, A Hen/Transactions of the Japan Society of Mechanical Engineers, Part A
Issue number762
Publication statusPublished - 2010 Feb
Externally publishedYes


  • Acoustic emission
  • Damage evaluation
  • Kernel method
  • Neural network
  • Selforganizing map
  • Solid oxide fuel cell

ASJC Scopus subject areas

  • General Materials Science
  • Mechanics of Materials
  • Mechanical Engineering


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