In this paper the potential of the principal component analysis(PCA) technique for the application of detecting leaks in water pipe networks was evaluated. For this purpose the PCA was conducted to evaluate the relevance of the calculated outliers of a PCA model utilizing the recorded pipe flows and the recorded pipe leak incidents of a case study water distribution system. The PCA technique was enhanced by applying the computational algorithms developed in this study which were designed to extract a partial set of flow data from the original 24 hour flow data so that the effective outlier detection rate was maximized. The relevance of the calculated outliers of a PCA model and the recorded pipe leak incidents was analyzed. The developed algorithm may be applied in determining further leak detection field work for water distribution blocks that have more than 70% of the effective outlier detection rate. However, the analysis suggested that further development on the algorithm is needed to enhance the applicability of the PCA in detecting leaks by considering series of leak reports happening in a relatively short period.

ABSTRACT
 1. 서 론
 2. 연구방법
  2.1 주성분 분석의 개념
  2.2 사용된 유량관측 자료
 3. 이상치 탐지유효율 분석
  3.1 24시간 유량자료를 이용한 PCA
  3.2 PCA의 관망 누수감지 적용성을 높일 수 있는 알고리즘
  3.3 이상치 탐지 유효율 분석결과
 4. 결 론
 References

• 김기민(부산대학교 공과대학 사회환경시스템공학과) | Kimin Kim (Department of Civil and Environmental Engineering, Pusan National University)
• 박수완(부산대학교 공과대학 사회환경시스템공학과) | Suwan Park (Department of Civil and Environmental Engineering, Pusan National University) Corresponding author