標題: Data driven modeling for power transformer lifespan evaluation
作者: Trappey, Charles V.
Trappey, Amy J. C.
Ma, Lin
Tsao, Wan-Ting
管理科學系
Department of Management Science
關鍵字: Condition based maintenance (CBM);prognostics and health management (PHM);logistic regression;remaining life prediction;sustainable engineering asset management
公開日期: 1-Mar-2014
摘要: Large sized power transformers are important parts of the power supply chain. These very critical networks of engineering assets are an essential base of a nation's energy resource infrastructure. This research identifies the key factors influencing transformer normal operating conditions and predicts the asset management lifespan. Engineering asset research has developed few lifespan forecasting methods combining real-time monitoring solutions for transformer maintenance and replacement. Utilizing the rich data source from a remote terminal unit (RTU) system for sensor-data driven analysis, this research develops an innovative real-time lifespan forecasting approach applying logistic regression based on the Weibull distribution. The methodology and the implementation prototype are verified using a data series from 161 kV transformers to evaluate the efficiency and accuracy for energy sector applications. The asset stakeholders and suppliers significantly benefit from the real-time power transformer lifespan evaluation for maintenance and replacement decision support.
URI: http://dx.doi.org/10.1007/s11518-014-5227-z
http://hdl.handle.net/11536/24003
ISSN: 1004-3756
DOI: 10.1007/s11518-014-5227-z
期刊: JOURNAL OF SYSTEMS SCIENCE AND SYSTEMS ENGINEERING
Volume: 23
Issue: 1
起始頁: 80
結束頁: 93
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