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.
Timely and accurate data-driven fault diagnosis approaches are essential for ensuring the reliable operation and efficient maintenance of rotating machinery. However, practical applications face ...
Astronomers have observed enormous filaments of galaxies tied together with dark matter — the stuff scientists believe makes up 85 percent of the total mass of the universe — stretching across ...
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