The method detects unknown faults in ultrasonic metal welding at 96% accuracy and incorporates new fault types from only five labeled samples to reach 98% classification accuracy.
Theissler, Detecting known and unknown faults in automotive systems using ensemble-based anomaly detection, Knowledge-Based Systems 123 (2017) 163–173
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Adaptive Unknown Fault Detection and Few-Shot Continual Learning for Condition Monitoring in Ultrasonic Metal Welding
The method detects unknown faults in ultrasonic metal welding at 96% accuracy and incorporates new fault types from only five labeled samples to reach 98% classification accuracy.