DOI QR코드

DOI QR Code

다중연결 해양부유체의 모형시험 구조응답 예측정확도 향상을 위한 유전알고리즘을 이용한 센서배치 최적화

Optimal Sensor Placement for Improved Prediction Accuracy of Structural Responses in Model Test of Multi-Linked Floating Offshore Systems Using Genetic Algorithms

  • 심기찬 (과학기술연합대학원대학교 선박해양플랜트연구소스쿨) ;
  • 이강수 (과학기술연합대학원대학교 선박해양플랜트연구소스쿨)
  • Kichan Sim (Korea Research Institute of Ships & Ocean Engineering School, University of Science & Technology) ;
  • Kangsu Lee (Korea Research Institute of Ships & Ocean Engineering School, University of Science & Technology)
  • 투고 : 2024.03.08
  • 심사 : 2024.04.30
  • 발행 : 2024.06.30

초록

본 논문에서는 다목적 구조물인 다중연결 해양부유체를 대상으로 변형 기반 모드 차수축소법을 적용하고 차수축소모델의 구조응답 예측 성능을 향상시키기 위해 유전 알고리즘 기반의 센서 배치 최적화를 수행하였다. 다중연결 해양부유체의 차수축소모델 생성에 필요한 변형 기반 모드 데이터를 얻기 위해 다양한 규칙파랑하중조건에 대한 유체-구조 연성 수치해석을 수행하고 변형 기반 모드의 직교성, 자기상관계수를 이용하여 주요 변형 기반 모드를 선정하였다. 다중연결 해양부유체의 경우 차수축소모델의 구조응답 예측 성능이 계측 및 예측 구조응답 위치에 따라 민감하기 때문에 유전 알고리즘 기반의 최적화를 수행하여 최적의 센서 배치를 도출하였다. 최적화 결과, 모든 센서 배치 조합에 대한 차수축소모델 생성 및 예측 성능 평가 대비 약 8배의 계산 비용을 절감하였으며, 예측 성능 평가 지표인 평균 제곱근 오차가 초기 센서 배치보다 84% 감소하였다. 또한, 다중연결 해양부유체 모형시험 결과를 이용하여 불규칙파랑하중에 대한 최적화된 센서 배치의 차수축소모델의 구조응답 예측 성능을 평가 및 검증하였다.

Structural health monitoring for ships and offshore structures is important in various aspects. Ships and offshore structures are continuously exposed to various environmental conditions, such as waves, wind, and currents. In the event of an accident, immense economic losses, environmental pollution, and safety problems can occur, so it is necessary to detect structural damage or defects early. In this study, structural response data of multi-linked floating offshore structures under various wave load conditions was calculated by performing fluid-structure coupled analysis. Furthermore, the order reduction method with distortion base mode was applied to the structures for predicting the structural response by using the results of numerical analysis. The distortion base mode order reduction method can predict the structural response of a desired area with high accuracy, but prediction performance is affected by sensor arrangement. Optimization based on a genetic algorithm was performed to search for optimal sensor arrangement and improve the prediction performance of the distortion base mode-based reduced-order model. Consequently, a sensor arrangement that predicted the structural response with an error of about 84.0% less than the initial sensor arrangement was derived based on the root mean squared error, which is a prediction performance evaluation index. The computational cost was reduced by about 8 times compared to evaluating the prediction performance of reduced-order models for a total of 43,758 sensor arrangement combinations. and the expected performance was overturned to approximately 84.0% based on sensor placement, including the largest square root error.

키워드

과제정보

본 논문은 선박해양플랜트연구소 기본사업"불확실성을 고려한 유탄성 기반 해양구조물 구조손상도평가 핵심기술 개발(5/5)"[PES5150]과 산업통상자원부 및 산업기술평가관리원(KEIT) 지원[20024292]에 의한 연구로 수행된 연구결과입니다.

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