Journal of Korean Society for Quality Management (품질경영학회지)

Korean Society for Quality Management (한국품질경영학회)
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Structural Quality Defect Discrimination Enhancement using Vertical Energy-based Wavelet Feature Generation

구조물의 품질 결함 변별력 증대를 위한 수직 에너지 기반의 웨이블릿 Feature 생성

  • Kim, Joon-Seok (Department of Business Administration, School of Business, Sejong University) ;
  • Jung, Uk (Department of Management, School of Business, Dongguk University)
  • 김준석 (세종대학교 경영학과) ;
  • 정욱 (동국대학교 경영학과)
  • Published : 2008.06.30
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Abstract

In this paper a novel feature extraction and selection is carried out in order to improve the discriminating capability between healthy and damaged structure using vibration signals. Although many feature extraction and selection algorithms have been proposed for vibration signals, most proposed approaches don't consider the discriminating ability of features since they are usually in unsupervised manner. We proposed a novel feature extraction and selection algorithm selecting few wavelet coefficients with higher class discriminating capability for damage detection and class visualization. We applied three class separability measures to evaluate the features, i.e. T test statistics, divergence, and Bhattacharyya distance. Experiments with vibration signals from truss structure demonstrate that class separabilities are significantly enhanced using our proposed algorithm compared to other two algorithms with original time-based features and Fourier-based ones.

Keywords

References

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