TY - GEN
T1 - Co-occurring cluster mining for damage patterns analysis of a fuel cell
AU - Inaba, Daiki
AU - Fukui, Ken Ichi
AU - Sato, Kazuhisa
AU - Mizusaki, Junichirou
AU - Numao, Masayuki
PY - 2012
Y1 - 2012
N2 - In this study, we research the mechanical correlations among components of solid oxide fuel cell (SOFC) by analyzing the co-occurrence of acoustic emission (AE) events which are caused by damage. Then we propose a novel method for mining patterns from the numerical data such as AE. The proposed method extracts patterns of two clusters considering co-occurrence between clusters and similarity within each cluster at the same time. In addition, we utilize the dendrogram obtained from hierarchical clustering for reduction of the search space. We applied the proposed method to AE data, and the damage patterns which represent the main mechanical correlations were extracted. We can acquire novel knowledge about damage mechanism of SOFC from the results.
AB - In this study, we research the mechanical correlations among components of solid oxide fuel cell (SOFC) by analyzing the co-occurrence of acoustic emission (AE) events which are caused by damage. Then we propose a novel method for mining patterns from the numerical data such as AE. The proposed method extracts patterns of two clusters considering co-occurrence between clusters and similarity within each cluster at the same time. In addition, we utilize the dendrogram obtained from hierarchical clustering for reduction of the search space. We applied the proposed method to AE data, and the damage patterns which represent the main mechanical correlations were extracted. We can acquire novel knowledge about damage mechanism of SOFC from the results.
KW - clustering
KW - co-occurrence pattern
KW - damage evaluation
UR - http://www.scopus.com/inward/record.url?scp=84861418665&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84861418665&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-30220-6_5
DO - 10.1007/978-3-642-30220-6_5
M3 - Conference contribution
AN - SCOPUS:84861418665
SN - 9783642302190
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 49
EP - 60
BT - Advances in Knowledge Discovery and Data Mining - 16th Pacific-Asia Conference, PAKDD 2012, Proceedings
T2 - 16th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2012
Y2 - 29 May 2012 through 1 June 2012
ER -