Hybrid Deep Learning Framework for Anomaly Detection in Power Plant Systems

Currently, thermal power units undertake the task of peak and frequency regulation, and their internal equipment is in a non-conventional environment, which could very easily fail and thus lead to unplanned shutdown of the unit. To realize the condition monitoring and early warning of the key equipm...

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Vydáno v:	Algorithms Ročník 18; číslo 11; s. 704
Hlavní autoři:	Wang, Shuchong, Zhao, Changxiang, Liu, Xingchen, Ni, Xianghong, Chen, Xu, Gao, Xinglong, Sun, Li
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Basel MDPI AG 01.11.2025
Témata:	Analysis Anomalies anomaly detection coal-fired power plant Coal-fired power plants Condition monitoring deep autoencoder Deep learning Electric power-plants Failure times False alarms Gaussian mixture model Laws, regulations and rules Learning Methods Nuclear energy Nuclear power plants Power plants Probabilistic models Superheaters Thermal power plants Transformer Turbines
ISSN:	1999-4893, 1999-4893
On-line přístup:	Získat plný text
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