TPA-AD generates boundary-near pseudo-anomalies via reconstruction, applies contrastive learning, and uses KNN to score anomalies in bearing time series with only normal training samples.
Tsay, Themis Palpanas, and Michael J
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TPA-AD: A Two-Stage Pseudo Anomaly-Guided Method for Bearing Time-Series Anomaly Detection
TPA-AD generates boundary-near pseudo-anomalies via reconstruction, applies contrastive learning, and uses KNN to score anomalies in bearing time series with only normal training samples.