Anomaly detection methods for infrequent failures in resistive steel welding

Many industrial plants encounter infrequent faults and failures (anomalies) during operation which generate significant increases in costs. Modelling and detection of these anomalies is challenging due to unbalanced (few anomalous observations) and unlabeled (no class information) historical data. Previous works require large, labeled, and balanced training datasets which are typically not available in industry. This work relies solely on data …