The noise in the acoustic emission (AE) signal must be removed to identify the mode of AE signal accurately. The Wavelet threshold de-noising method shows some unique advantages. Based on the threshold selection risky problem, K-means clustering method was used to classify the high-frequency coefficients by the wavelet decomposition to determine the removal threshold for the wavelet coefficients corresponding to the noise, and achieve the de-noising purpose. Hard-threshold method and soft-threshold method were applied to AE signal through the wavelet threshold de-noising. The thresholds generated by K-means clustering approach and the Donoho method improved were respectively used as the threshold for the de-noising of the wavelet coefficients. The experimental results show that the method proposed is superior to the Donoho method improved in the three indicators of signal to noise ratio, root mean square error.
목차
Abstract 1. Introduction 2. The Transform of One-Dimensional Discrete Wavelet 3. The Method of Wavelet Threshold De-noising 4. The Wavelet De-noising Threshold Generation Based on K-Means Clustering Method 5. The Results and Analysis of Experiments 6. Conclusion References
보안공학연구지원센터(IJMUE) [Science & Engineering Research Support Center, Republic of Korea(IJMUE)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Multimedia and Ubiquitous Engineering
간기
월간
pISSN
1975-0080
수록기간
2008~2016
등재여부
SCOPUS
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Multimedia and Ubiquitous Engineering Vol.10 No.7