Co-occurring cluster mining for damage patterns analysis of a fuel cell

Daiki Inaba; Ken Ichi Fukui; Kazuhisa Sato; Junichirou Mizusaki; Masayuki Numao

doi:10.1007/978-3-642-30220-6_5

Co-occurring cluster mining for damage patterns analysis of a fuel cell

Daiki Inaba, Ken Ichi Fukui, Kazuhisa Sato, Junichirou Mizusaki, Masayuki Numao

ENG - Fracture and Reliability Research Institute

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	Advances in Knowledge Discovery and Data Mining - 16th Pacific-Asia Conference, PAKDD 2012, Proceedings
Pages	49-60
Number of pages	12
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-30220-6_5
Publication status	Published - 2012
Event	16th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2012 - Kuala Lumpur, Malaysia Duration: 2012 May 29 → 2012 Jun 1

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	7301 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	16th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2012
Country/Territory	Malaysia
City	Kuala Lumpur
Period	12/5/29 → 12/6/1

Keywords

clustering
co-occurrence pattern
damage evaluation

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-642-30220-6_5

Cite this

Inaba, D., Fukui, K. I., Sato, K., Mizusaki, J., & Numao, M. (2012). Co-occurring cluster mining for damage patterns analysis of a fuel cell. In Advances in Knowledge Discovery and Data Mining - 16th Pacific-Asia Conference, PAKDD 2012, Proceedings (PART 2 ed., pp. 49-60). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7301 LNAI, No. PART 2). https://doi.org/10.1007/978-3-642-30220-6_5

Co-occurring cluster mining for damage patterns analysis of a fuel cell. / Inaba, Daiki; Fukui, Ken Ichi; Sato, Kazuhisa et al.

Advances in Knowledge Discovery and Data Mining - 16th Pacific-Asia Conference, PAKDD 2012, Proceedings. PART 2. ed. 2012. p. 49-60 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7301 LNAI, No. PART 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Inaba, D, Fukui, KI, Sato, K, Mizusaki, J & Numao, M 2012, Co-occurring cluster mining for damage patterns analysis of a fuel cell. in Advances in Knowledge Discovery and Data Mining - 16th Pacific-Asia Conference, PAKDD 2012, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 7301 LNAI, pp. 49-60, 16th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2012, Kuala Lumpur, Malaysia, 12/5/29. https://doi.org/10.1007/978-3-642-30220-6_5

Inaba D, Fukui KI, Sato K, Mizusaki J, Numao M. Co-occurring cluster mining for damage patterns analysis of a fuel cell. In Advances in Knowledge Discovery and Data Mining - 16th Pacific-Asia Conference, PAKDD 2012, Proceedings. PART 2 ed. 2012. p. 49-60. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-30220-6_5

Inaba, Daiki ; Fukui, Ken Ichi ; Sato, Kazuhisa et al. / Co-occurring cluster mining for damage patterns analysis of a fuel cell. Advances in Knowledge Discovery and Data Mining - 16th Pacific-Asia Conference, PAKDD 2012, Proceedings. PART 2. ed. 2012. pp. 49-60 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

@inproceedings{2536cd36d95f496abd42d0ae0a731fb9,

title = "Co-occurring cluster mining for damage patterns analysis of a fuel cell",

abstract = "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.",

keywords = "clustering, co-occurrence pattern, damage evaluation",

author = "Daiki Inaba and Fukui, {Ken Ichi} and Kazuhisa Sato and Junichirou Mizusaki and Masayuki Numao",

year = "2012",

doi = "10.1007/978-3-642-30220-6_5",

language = "English",

isbn = "9783642302190",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

number = "PART 2",

pages = "49--60",

booktitle = "Advances in Knowledge Discovery and Data Mining - 16th Pacific-Asia Conference, PAKDD 2012, Proceedings",

edition = "PART 2",

note = "16th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2012 ; Conference date: 29-05-2012 Through 01-06-2012",

}

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 -

Co-occurring cluster mining for damage patterns analysis of a fuel cell

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this