Real-time Adaptation for Condition Monitoring Signal Prediction using Label-aware Neural Processes

arXiv:2403.16377v1 Announce Type: new
Abstract: Building a predictive model that rapidly adapts to real-time condition monitoring (CM) signals is critical for engineering systems/units. Unfortunately, many current methods suffer from a trade-off between representation power and agility in online settings. For instance, parametric methods that assume an underlying functional form for CM signals facilitate efficient online prediction updates. However, this simplification leads to vulnerability to model specifications and an inability to capture complex signals. On the other hand, approaches based on …

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