The objective of this study is to evaluate the mechanical behaviors and structural integrity of the weldment of high strength steel by using an acoustic emission (AE) techniques. Simple tension and AE tests were conducted against the 3 kind of welding test specimens. In order to analysis the effectiveness of weldability, joinability and structural integrity, we used K-means clustering method as a unsupervised learning pattern recognition algorithm for obtained multivariate AE main data sets, such as AE counts, energy, amplitude, hits, risetime, duration, counts to peak and rms signals. Through the experimental results, the effectiveness of the proposed method is discussed.

Abstract
 1. 서론
 2. 관련 이론
  2.1 음향방출(acoustic emission)
  2.2 패턴인식(pattern recognition)
 3. 실험재료 및 실험방법
  3.1 실험재료 및 시험편
  3.2 실험방법
 4. 실험결과 및 고찰
 5. 결론
 6. 참고문헌

• 김길동 | Kim Gil-Dong
• 이장규 | Rhee Zhang-Kyu