대한전자공학회논문지SP (Journal of the Institute of Electronics Engineers of Korea SP)

대한전자공학회 (The Institute of Electronics and Information Engineers)
권호 표지

음향방출을 이용한 금속의 피로 균열성장 패턴인식 기법

A Pattern Recognition Method of Fatigue Crack Growth on Metal using Acoustic Emission

  • 이수일 (한국과학기술원 전자전산학부) ;
  • 이종석 (한국과학기술원 전자전산학부) ;
  • 민황기 (한국과학기술원 전자전산학부) ;
  • 박철훈 (한국과학기술원 전자전산학부)
  • Lee, Soo-Ill (School of Electrical Engineering and Computer Science, KAIST) ;
  • Lee, Jong-Seok (School of Electrical Engineering and Computer Science, KAIST) ;
  • Min, Hwang-Ki (School of Electrical Engineering and Computer Science, KAIST) ;
  • Park, Cheol-Hoon (School of Electrical Engineering and Computer Science, KAIST)
  • 발행 : 2009.05.25
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초록

음향방출 기법은 작동중인 상태에서 기계 설비를 비파괴 검사할 수 있는 기법이며, 균열성장 같은 장애의 신뢰성 있는 감시를 위해서 순간적인 균열신호뿐만 아니라 동특성을 이용하는 것이 중요하다. 균열성장을 검출하기 위해 널리 사용되는 물리적 파괴 3단계는 음향방출 현상이 시간에 따라 서로 겹치는 문제점이 있어 정확한 균열성장 시간을 추정하기 어렵다. 제안한 패턴인식 기법은 오경보와 미탐지를 최소화하기 위해서 음향방출 동특성을 입력으로 사용하고, 균열성장 시간을 정확히 추정하기 위해 시간에 따른 클러스터링 기법을 사용한다. 실험결과는 제안한 패턴인식 기법이 압력의 변화에 의한 음향방출의 변화의 강인함 때문에 실용화에 효율적임을 보여준다.

Acoustic emission-based techniques are being used for the nondestructive inspection of mechanical systems used in service. For reliable fault monitoring related to the crack growth, it is important to identify the dynamical characteristics as well as transient crack-related signals. Widely used methods which are based on physical phenomena of the three damage stages for detecting the crack growth have a problem that crack-related acoustic emission activities overlap in time, therefore it is insufficient to estimate the exact crack growth time. The proposed pattern recognition method uses the dynamical characteristics of acoustic emission as inputs for minimizing false alarms and miss alarms and performs the temporal clustering to estimate the crack growth time accurately. Experimental results show that the proposed method is effective for practical use because of its robustness to changes of acoustic emission caused by changes of pressure levels.

키워드

참고문헌

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