Abstract: This work considers a state estimation problem in modern power systems, e.g., smart grids. Due to the use of digital technology, the smart grids often encounter malicious data that is ...
Transfer Learning for Anomaly Detection in Rotating Machinery Using Data-Driven Key Order Estimation
Abstract: The detection of anomalous behavior of an engineered system or its components is an important task for enhancing reliability, safety, and efficiency across various engineering applications.
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