Depth-Based Condition Monitoring and Contributing Factor Analysis for Anomalies in Combined Cycle Power Plant

Unexpected fault or failure in the power plant have caused high maintenance costs, the loss of energy production, and even safety issues. Developments in sensor technologies and data analytics have aided proper preventive maintenance actions for the system to improve asset availability and reduce re...

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Bibliographic Details
Published in:	IEEE access Vol. 12; pp. 73400 - 73412
Main Authors:	Lim, Munwon, Kim, Yunhee, Jin, Shengxin, Ha, Sangwoo, Yong Chang, Sung, Su Kang, Hae, Sang Park, Gyu, Lee Joo, Mi, Jung, Chang-Sik, Cho, Youngjin, Bae, Suk Joo
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Analytical models Anomalies Anomaly detection Biomedical monitoring causal inference Clustering Clustering algorithms Combined cycle power generation Condition monitoring condition-based maintenance contribution scores Discriminant analysis Energy costs Factor analysis health monitoring Maintenance Maintenance costs Medical services Monitoring Power generation Power plants Preventive maintenance Process parameters Process variables Repair & maintenance Turbines
Online Access:	Get full text
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