A Novel Fault Detection with Minimizing the Noise-Signal Ratio Using Reinforcement Learning.
Dapeng ZhangZhiling LinZhiwei GaoPublished in: Sensors (2018)
Keyphrases
- fault detection
- vibration signal
- reinforcement learning
- condition monitoring
- random noise
- industrial processes
- fault diagnosis
- fault identification
- additive noise
- low signal to noise ratio
- tennessee eastman
- signal detection
- robust fault detection
- low frequency
- fault detection and diagnosis
- high frequency
- failure detection
- noise ratio
- state space
- fuel cell
- power spectrum
- operating conditions
- power plant
- frequency domain
- fault localization
- fault isolation
- received signal
- wavelet transform
- machine learning
- autoregressive
- signal to noise ratio
- learning algorithm
- median filter
- underwater vehicles
- fault detection and isolation
- non stationary
- decision support system