PHM

This work proposes a method for developing equipment lifespan estimators that combine incomplete physical and numerical information.

This work proposes a methodology for developing deterioration models to estimate the remaining lifetime of a system using physics-informed learning (PIL).

This work proposes a method for designing simple models of the remaining lifetime of a system.

This work presents a novel approach for unsupervised anomaly detection based on word embeddings using time series data represented as text.

This work presents a model of the running resistance of a locomotive powered by liquefied natural gas.

This work proposes a novel approach based on variational encoding to evaluate aircraft engine monitoring data.

This work presents RUL-RVE, a Python tool for the assessment of Remaining Useful Life (RUL) that can achieve remarkable forecast accuracy while providing an interpretable assessment.

This work presents a novel recurrent VAE-based framework for the assessment of Engine Health Monitoring (EHM) data in aircraft.