The identification of low fatigue damage using fuzzy double clustering framework

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Identifying damaging or non-damaging events in long records of fatigue data is a crux of recapitulating pristine data. In this article, a fuzzy double clustering framework (DCf) is utilized to classify the fatigue segment by exploiting two typical statistical features; kurtosis and the standard deviation. In the first stage, segments are assigned to a number of similar groups to generate multi-dimensional prototypes. Then, the resulting multi-dimensional prototypes are projected onto each featuring space of the input variables. On each dimension, a hierarchical clustering is applied to extract the information granules. For ease of interpretability, the granules are translated into a set of antecedent-consequent rules by means of a fuzzy set theory where for the model output, two distinct classes namely low and high with different degrees of evidence are assigned. The results reveal that the fatigue segments could be classified according to the value of kurtosis and standard deviation in a specific range where further, it can be a part of a fatigue data editing process.

Original languageEnglish
Title of host publicationProceedings - 2011 IEEE 7th International Colloquium on Signal Processing and Its Applications, CSPA 2011
Pages181-186
Number of pages6
DOIs
Publication statusPublished - 2011
Event2011 IEEE 7th International Colloquium on Signal Processing and Its Applications, CSPA 2011 - Penang
Duration: 4 Mar 20116 Mar 2011

Other

Other2011 IEEE 7th International Colloquium on Signal Processing and Its Applications, CSPA 2011
CityPenang
Period4/3/116/3/11

Fingerprint

Fatigue damage
Fatigue of materials
Information granules
Fuzzy set theory

Keywords

  • classification
  • clustering
  • fatigue segment
  • fuzzy rule

ASJC Scopus subject areas

  • Signal Processing

Cite this

Mohd Nopiah, Z., Osman, M. H., Abdullah, S., & Baharin, M. N. (2011). The identification of low fatigue damage using fuzzy double clustering framework. In Proceedings - 2011 IEEE 7th International Colloquium on Signal Processing and Its Applications, CSPA 2011 (pp. 181-186). [5759869] https://doi.org/10.1109/CSPA.2011.5759869

The identification of low fatigue damage using fuzzy double clustering framework. / Mohd Nopiah, Zulkifli; Osman, Mohd Haniff; Abdullah, Shahrum; Baharin, M. N.

Proceedings - 2011 IEEE 7th International Colloquium on Signal Processing and Its Applications, CSPA 2011. 2011. p. 181-186 5759869.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Mohd Nopiah, Z, Osman, MH, Abdullah, S & Baharin, MN 2011, The identification of low fatigue damage using fuzzy double clustering framework. in Proceedings - 2011 IEEE 7th International Colloquium on Signal Processing and Its Applications, CSPA 2011., 5759869, pp. 181-186, 2011 IEEE 7th International Colloquium on Signal Processing and Its Applications, CSPA 2011, Penang, 4/3/11. https://doi.org/10.1109/CSPA.2011.5759869
Mohd Nopiah Z, Osman MH, Abdullah S, Baharin MN. The identification of low fatigue damage using fuzzy double clustering framework. In Proceedings - 2011 IEEE 7th International Colloquium on Signal Processing and Its Applications, CSPA 2011. 2011. p. 181-186. 5759869 https://doi.org/10.1109/CSPA.2011.5759869
Mohd Nopiah, Zulkifli ; Osman, Mohd Haniff ; Abdullah, Shahrum ; Baharin, M. N. / The identification of low fatigue damage using fuzzy double clustering framework. Proceedings - 2011 IEEE 7th International Colloquium on Signal Processing and Its Applications, CSPA 2011. 2011. pp. 181-186
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