Fault Diagnosis using eXplainable AI: a Transfer Learning-based Approach for Rotating Machinery exploiting Augmented Synthetic Data.
Lucas Costa BritoGian Antonio SustoJorge Nei BritoMarcus Antonio Viana DuartePublished in: CoRR (2022)
Keyphrases
- synthetic data
- rotating machinery
- transfer learning
- fault diagnosis
- expert systems
- fault detection
- machine learning
- knowledge transfer
- labeled data
- artificial intelligence
- reinforcement learning
- neural network
- collaborative filtering
- fuzzy logic
- fault detection and diagnosis
- active learning
- text classification
- power transformers
- semi supervised learning
- data sets
- transfer knowledge
- operating conditions
- multi sensor information fusion
- cross domain
- gas turbine
- real world
- analog circuits
- computational intelligence
- real image data
- multiple faults
- electronic equipment
- target domain
- text categorization
- intelligent systems
- real time
- power plant
- text mining
- similarity measure
- information fusion
- unlabeled data
- knowledge base