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.
Abstract: We propose an anomaly detection method based on modal representation and a noise-robust sparse sensor position optimization method. We focus on the detection of anomalies in global sea ...
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