Machine Learning for Condition Monitoring and Innovation.
Niels Henrik PontoppidanTue Lehn-SchiølerKaare Brandt PetersenPublished in: ICASSP (2019)
Keyphrases
- condition monitoring
- machine learning
- fault detection
- fault diagnosis
- acoustic emission
- nuclear power plant
- machine learning methods
- case study
- data mining
- computer vision
- knowledge acquisition
- power transformers
- pattern recognition
- learning algorithm
- information extraction
- feature selection
- machine learning algorithms
- active learning
- artificial intelligence
- knowledge management
- text classification
- decision trees
- steady state
- inductive logic programming
- decision support system
- speech recognition
- decision makers
- computational intelligence
- natural language processing
- expert systems
- computer science
- reinforcement learning
- image processing