상세정보
학술대회
An Approach for Utilizing Correlation among Sensors for Unsupervised Anomaly Detection of Wind Turbine System
- 발행일
- 202110
- 출처
- International Conference on Information and Communication Technology Convergence (ICTC) 2021, pp.104-109
- 협약과제
- 21ZK1100, 호남권 지역산업 기반 ICT 융합기술 고도화 지원사업, 이길행
- 초록
- An anomaly detection model needs to be built by considering the characteristics of a target system. In this paper, we study unsupervised anomaly detection for a wind turbine system. A wind turbine system has many components and sensors of the same components are highly correlated. Considering these characteristics of a wind turbine system, our approach for unsupervised anomaly detection is to utilize correlation among sensors. We first generate a standard correlation matrix (i.e., the most representative normal correlation matrix) from the given normal data. Then, we measure a distance between the standard matrix and a correlation matrix of a target test data using mean squared error as an anomaly score. Through experiments using real wind turbine system data, we show that our unsupervised approach achieves a maximum of 0.928 ROC AUC (0.894 on average),
- KSP 제안 키워드
- Detection model, Test data, Unsupervised Approach, Wind Turbine system, anomaly score, correlation matrix, mean square error(MSE), unsupervised anomaly detection