Unsupervised anomaly detection of the gas turbine operation via convolutional auto-encoder.
Geunbae LeeMyungkyo JungMyoungwoo SongJaegul ChooPublished in: ICPHM (2020)
Keyphrases
- gas turbine
- unsupervised anomaly detection
- anomaly detection
- fault diagnosis
- power plant
- fault tree
- intrusion detection
- semi supervised
- operating conditions
- bit rate
- low complexity
- fault detection
- rate distortion
- motion estimation
- neural network
- deep learning
- data sets
- pairwise
- simulation model
- steady state
- real time
- machine learning
- model selection
- markov chain