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: Expert Syst. Appl. (2023)
Keyphrases
- rotating machinery
- synthetic data
- transfer learning
- fault diagnosis
- expert systems
- fault detection
- machine learning
- artificial intelligence
- knowledge transfer
- data sets
- reinforcement learning
- cross domain
- neural network
- labeled data
- fuzzy logic
- real image data
- transfer knowledge
- fault detection and diagnosis
- electronic equipment
- semi supervised learning
- text categorization
- text classification
- real world
- active learning
- intelligent systems
- text mining
- power transformers
- chemical process
- gas turbine
- operating conditions
- monitoring and fault diagnosis
- collaborative filtering
- machine learning algorithms
- target domain
- learning algorithm
- knowledge base
- multiple faults
- real time
- analog circuits
- semi supervised
- artificial neural networks
- learning process
- knowledge discovery
- multi sensor information fusion