Visualization of Damage Progress in Solid Oxide Fuel Cells
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概要
- 論文の詳細を見る
The fuel cell is regarded as a highly efficient, low-pollution power generation system. In particular, Solid Oxide Fuel Cell (SOFC) has a high generation efficiency. However, a crucial issue in putting SOFC to practical use is the establishment of a technique for evaluating the deterioration. We previously developed a technique by which to measure the mechanical damage of SOFC using the Acoustic Emission (AE) method. In the present paper, we applied the kernel Self-Organizing Map (SOM), which is an extended neural network model, to produce a cluster map reflecting the similarity of AE events. The obtained map visualized the change in occurrence patterns of similar AE events, revealing four phases of damage progress. The methodology of the present study provides a common foundation for a comprehensive damage evaluation system and a damage monitoring system.
著者
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Mizusaki Junichiro
Institute Of Multidisciplinary Research For Advanced Materials Tohoku University
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Numao Masayuki
The Institute Of Scientific And Industrial Research Osaka University
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Sato Kazuhisa
Institute For Materials Research Tohoku University
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MIZUSAKI Junichiro
Institute of Multidisciplinary Research for Advanced Materials, Tohoku University
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MORIYAMA Koichi
The Institute of Scientific and Industrial Research, Osaka University
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FUKUI Ken-ichi
The Institute of Scientific and Industrial Research, Osaka University
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AKASAKI Shogo
Graduate School of Information Science and Technology, Osaka University
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KURIHARA Satoshi
The Institute of Scientific and Industrial Research, Osaka University
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