Analysis and Classification of Acoustic Emission Signals During Wood Drying Using the Principal Component Analysis

주성분 분석을 이용한 목재 건조 중 발생하는 음향방출 신호의 해석 및 분류

  • 강호양 (충남대학교 농업생명과학대학 임산공학과) ;
  • 김기복 (한국표준과학연구원 환경 안전계측연구센터)
  • Published : 2003.06.30

Abstract

In this study, acoustic emission (AE) signals due to surface cracking and moisture movement in the flat-sawn boards of oak (Quercus Variablilis) during drying under the ambient conditions were analyzed and classified using the principal component analysis. The AE signals corresponding to surface cracking showed higher in peak amplitude and peak frequency, and shorter in rise time than those corresponding to moisture movement. To reduce the multicollinearity among AE features and to extract the significant AE parameters, correlation analysis was performed. Over 99% of the variance of AE parameters could be accounted for by the first to the fourth principal components. The classification feasibility and success rate were investigated in terms of two statistical classifiers having six independent variables (AE parameters) and six principal components. As a result, the statistical classifier having AE parameters showed the success rate of 70.0%. The statistical classifier having principal components showed the success rate of 87.5% which was considerably than that of the statistical classifier having AE parameters.

본 연구는 목재(참나무 판목 판재) 건조 중 발생하는 음향방출 신호에 대하여 목재 내 수분이동에 의한 신호와 표면할열에 의한 신호를 해석하고 분류하기 위하여 수행되었다. AE 신호의 특징값들에 대한 상관분석을 실시하여 상호의존성이 높은 변수를 제거한 후 주성분 분석을 실시하였다. AE 변수들을 독립변수로 한 분류기와 주성분들을 독립변수로 한 분류기에 대하여 분류성능을 비교하였다. 목재 건조 시 발생하는 표면할열과 수분이동에 따른 AE 신호 파형을 분석한 결과 대체적으로 표면할열에 의한 신호가 최대진폭이 크며 상승시간이 팎고 상대적으로 고주파의 신호인 것으로 분석되었다. 다중 회귀분석모델을 이용하여 수분이동에 의한 신호와 표면할열에 의한 신호를 분류할 수 있는 분류기를 개발하고 평가한 결과 개별 AE 변수들을 독립변수로 하는 분류기 보다 주성분들을 독립변수로 하는 분류기의 분류성능이 양호한 것으로 나타났다.

Keywords

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