음향방출 원신호를 이용한 저항점용접의 품질평가에 관한 연구
(주)코리아스칼라
- 최초 등록일
- 2016.04.02
- 최종 저작일
- 2014.04
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서지정보
ㆍ발행기관 : 한국기계기술학회
ㆍ수록지정보 : 한국기계기술학회지 / 16권 / 2호
ㆍ저자명 : 우창기, 이장규
목차
Abstract
1. 서론
2. 관련 이론
2.1 웨이블릿 변환
2.2 역전파 신경망
3. 실험 및 방법
4. 실험결과 및 신호해석
5. 결론
후기
References
영어 초록
To estimate weld quality of the resistance spot-welding, the acoustic emission features are investigated from the total acoustic emission signal at the single-spot weld. Typically, the resistance spot welding process consists of several stages: set-down of the electrodes, squeeze, current flow, forging, hold time, and lift-off. Various types of acoustic emission response corresponding to each stage can be separately analyzed by using back-propagation neural network classifier and wavelet transform technique. The presented machine learning results provide a validation for using back-propagation neural network and wavelet transform technique as a valuable insights into the resistance spot-welding process. Especially, a wavelet transform technique is demonstrated and the plots are very powerful in the recognition of the acoustic emission features
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