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Authors: Masahiro Tsunoyama 1 ; Yuki Imai 1 ; Hayato Hori 2 ; Hirokazu Jinno 2 ; Masayuki Ogawa 2 and Tatsuo Sato 2

Affiliations: 1 Niigata Institute of Technology, Japan ; 2 Flowserve Japan Co. andLtd, Japan

Keyword(s): Fuzzy Measure, Fuzzy Integral, Fault Diagnosis, Vibration Diagnosis.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Computer-Supported Education ; Domain Applications and Case Studies ; Fuzzy Systems ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Industrial, Financial and Medical Applications ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Soft Computing and Intelligent Agents ; System Identification and Fault Detection ; Theory and Methods

Abstract: This paper proposes an identification method of fuzzy measure for fault diagnosis of rotating machineries using vibration spectra method. The membership degrees for spectra in fuzzy set composed of vibration spectra are obtained from the optimized membership functions. The fuzzy measure is identified by the proposed method using the partial correlation coefficients between two spectra and the weight of each spectrum given by skilled engineers. The possibility of faults are determined by the fuzzy integral that is made by using the membership degrees and fuzzy measures for spectra. This paper also evaluates the method using field data.

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Paper citation in several formats:
Tsunoyama, M.; Imai, Y.; Hori, H.; Jinno, H.; Ogawa, M. and Sato, T. (2013). Identification of Fuzzy Measures for Machinery Fault Diagnosis. In Proceedings of the 5th International Joint Conference on Computational Intelligence (IJCCI 2013) - FCTA; ISBN 978-989-8565-77-8; ISSN 2184-3236, SciTePress, pages 273-278. DOI: 10.5220/0004629202730278

@conference{fcta13,
author={Masahiro Tsunoyama. and Yuki Imai. and Hayato Hori. and Hirokazu Jinno. and Masayuki Ogawa. and Tatsuo Sato.},
title={Identification of Fuzzy Measures for Machinery Fault Diagnosis},
booktitle={Proceedings of the 5th International Joint Conference on Computational Intelligence (IJCCI 2013) - FCTA},
year={2013},
pages={273-278},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004629202730278},
isbn={978-989-8565-77-8},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the 5th International Joint Conference on Computational Intelligence (IJCCI 2013) - FCTA
TI - Identification of Fuzzy Measures for Machinery Fault Diagnosis
SN - 978-989-8565-77-8
IS - 2184-3236
AU - Tsunoyama, M.
AU - Imai, Y.
AU - Hori, H.
AU - Jinno, H.
AU - Ogawa, M.
AU - Sato, T.
PY - 2013
SP - 273
EP - 278
DO - 10.5220/0004629202730278
PB - SciTePress

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