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2024 Vol.40, Issue 4 Preview Page
Study on Outlier Analysis Considering the Spatial Distribution of Intelligent Compaction Measurement Values

지능형 다짐값의 공간적 분포를 고려한 이상치 분석 기법 연구

Taek-Kyu Chung1
,
Jin-Woo Cho2
,
Choong-Ki Chung3
,
Sung-Ha Baek4*
정 택규1
,
조 진우2
,
정 충기3
,
백 성하4*
1Member, Ph.D. Student, Department of Civil and Environmental Engineering, Seoul National Univ.
2Member, Research Fellow, Department of Geotechnical Engineering, Korea Institute of Civil Engineering and Building Technology
3Member, Prof., Department of Civil and Environmental Engineering, Seoul National Univ.
4Member, Assistant Prof., School of Civil and Environmental Engineering & Construction Engineering Research Institute, Hankyong National Univ.
1정회원, 서울대학교 건설환경공학부 박사과정
2정회원, 한국건설기술연구원 지반연구본부 연구위원
3정회원, 서울대학교 건설환경공학부 교수
4정회원, 한경국립대학교 건설환경공학부 조교수
*Corresponding Author
31 August 2024. pp. 91-103
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Abstract

In this study, we propose an outlier detection method that considers the spatial distribution of intelligent compaction measurement values (ICMVs) to address the high variability of ICMVs measured continuously across an entire construction area. The proposed method initially identified cases where the CMV at a specific location decreased despite an increase in the number of compaction passes. Among these, values that significantly differed from those measured within a 1.5-m radius were classified as outliers. Applying this method to CMV data obtained from field tests, we found that it effectively excluded the influence of changes in roller operating conditions unrelated to compaction quality while considering the inherent heterogeneity of the soil. However, after removing the outliers, the coefficient of variation of CMV (21.4%-26.3%) remained higher than the 20% suggested by relevant standards. Further field tests are needed to modify the proposed outlier detection method and to establish reasonable criteria for the variability of ICMV.

Keywords
CMV
Earthwork
Intelligent compaction
Outlier analysis
Spatial distribution

본 연구에서는 전체 시공영역에 대해 연속적으로 도출되는 지능형 다짐값의 높은 변동성과 관련한 문제를 해결하기 위해서, 지능형 다짐값의 공간적 분포를 고려한 이상치 분석 기법을 제안하였다. 제안된 기법에서는 다짐횟수 증가에도 불구하고 특정 위치에서 측정된 CMV가 감소하는 경우를 1차적으로 선별하고, 유효반경 1.5m 내에서 측정된 값들과의 차이가 큰 값들을 이상치로 판별한다. 본 연구에서 제안된 이상치 분석 기법을 현장시험에서 측정된 CMV 데이터에 적용한 결과, 지반의 내재적 불균질성은 고려하면서 다짐 품질과 관계없는 다짐롤러 구동조건의 변화에 따른 영향만을 배제할 수 있는 것으로 나타났다. 이상치 제거 후 CMV의 변동계수는 21.4~26.3%로 산정되었으며 관련 기준(20%)에서 제시하고 있는 수치보다 크게 나타났다. 추후 제안된 이상치 분석 기법에 여러 현장시험 데이터를 적용하여 고도화하고 지능형 다짐값의 변동성에 대한 합리적인 기준을 제안해야 할 것으로 판단된다.

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Information
  • Publisher :The Korean Geotechnical Society
  • Publisher(Ko) :한국지반공학회
  • Journal Title :Journal of the Korean Geotechnical Society
  • Journal Title(Ko) :한국지반공학회 논문집
  • Volume : 40
  • No :4
  • Pages :91-103
  • Received Date : 2024-07-08
  • Revised Date : 2024-08-01
  • Accepted Date : 2024-08-06
  • DOI :https://doi.org/10.7843/kgs.2024.40.4.91
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