Anomaly Detection of Power Plant Equipment Using Long Short-Term Memory Based Autoencoder Neural Network

Anomaly Detection of Power Plant Equipment Using Long Short-Term Memory Based Autoencoder Neural Network

Anomaly detection is of great significance in condition-based maintenance of power plant equipment. The conventional fixed threshold detection method is not able to perform early detection of equipment abnormalities. In this study, a general anomaly detection framework based on a long short-term mem...

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Bibliographic Details
Main Authors: Di Hu, Chen Zhang, Tao Yang, Gang Chen
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Sensors
Subjects:
anomaly detection
power plant
artificial neural networks
long short-term memory based autoencoder neural networks
normal behavior model
Online Access:https://www.mdpi.com/1424-8220/20/21/6164

Internet

https://www.mdpi.com/1424-8220/20/21/6164

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