The Journal of the Convergence on Culture Technology (문화기술의 융합)

The International Promotion Agency of Culture Technology (국제문화기술진흥원)
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Improvement of SOC Structure Automated Measurement Analysis Method through Probability Analysis of Time-History Data

시계열 데이터의 확률분석을 통한 SOC 구조물 자동화계측 분석기법 개선

  • Received : 2022.12.28
  • Accepted : 2023.01.09
  • Published : 2023.01.31
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Abstract

Currently, large-scale and deep-depth excavation construction is being carried out in the vicinity of structures due to overdensity in urban areas in Korea. It is very important to secure the safety of retaining structures and underground structures for adjacent excavation work in urban areas. The safety of facilities is managed by introducing an automated measurement system. However, the utilization of the results of the automated measurement system is very low. Conventional evaluation techniques rely only on the maximum value of the measured data, and can overestimate abnormal behavior. In this study, we intend to improve the analysis technique for the automation measurement results. In order to identify abnormal behavior of facilities, a time-series analysis method for automated measurement data was presented. By applying a probability statistical analysis technique to a vast amount of data, highly reliable results were derived. In this study, the analysis method and evaluation method that can process the vast amount of data of facilities have been improved.

현재 우리나라는 도심지 과밀도로 구조물과 인접하여 대규모, 대심도 굴착시공이 이루어지고 있다. 도심지에서의 인접굴착공사는 흙막이 구조물 및 지하구조물의 안전성 확보가 매우 중요하다. 이에 자동화계측 시스템을 도입하여 시설물에 대한 안전성을 관리하고 있다. 그러나 자동화계측 시스템 결과의 활용도는 매우 낮은 실정이다. 종래 평가기법은 측정된 데이터의 최댓값에만 의존하여, 이상 거동을 과대 평가할 수 있는 기법이다. 본 연구에서는 자동화계측 결과에 대한 분석기법을 개선하고자 한다. 시설물의 이상거동을 파악하기 위해 자동화계측 데이터 시계열 분석기법을 제시하였다. 또한 방대한 양의 데이터를 확률통계 분석기법을 적용하여 신뢰성 높은 결과를 도출하였다. 따라서 본 연구에서는 시설물의 방대한 양의 데이터를 처리할 수 있는 분석기법 및 평가기법을 개선하였다.

Keywords

Acknowledgement

이 논문은 2022년도 정부(과학기술정보통신부)의 재원으로 정보통신기획평가원의 지원을 받아 수행된 연구임 (No. 2022-0-00829, 스킨센서와 A.I.를 활용한 SOC 시설물 실시간 이상 감지 시스템 개발)

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