fastICA 기반 발전기 고장 진단 및 예측Failure Diagnosis and Prediction for a Thermal Power Plant Generator using fastICA
- Other Titles
- Failure Diagnosis and Prediction for a Thermal Power Plant Generator using fastICA
- Authors
- 채선규; 김규리; 배병용; 배석주
- Issue Date
- Dec-2021
- Publisher
- 한국신뢰성학회
- Keywords
- Thermal Power Plant; Prognostics and Health Management; Control Chart; Dimension Reduction
- Citation
- 신뢰성 응용연구, v.21, no.4, pp.341 - 351
- Indexed
- KCI
- Journal Title
- 신뢰성 응용연구
- Volume
- 21
- Number
- 4
- Start Page
- 341
- End Page
- 351
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/138554
- DOI
- 10.33162/JAR.2021.12.21.4.341
- ISSN
- 1738-9895
- Abstract
- Purpose: Failure in thermal power plant generators has high safety and financial risk. Diagnostics and Prognostics to detect abnormality in advance are crucial for failure prevention.
Methods: In this research, fast independent component analysis was applied to select key features from sensor data, and abnormalities were detected when unnatural variation existed in multivariate control charts.
Results: The proposed framework was applied to the dataset acquired from a thermal power plant, and exhibited promising results in detecting and predicting incipient failures.
Conclusion: From the analytical results of an example, it was found that the proposed methodology has potential in failure diagnostics and prognostics to increase the availability of facilities through early detection of incipient failures.
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