Feature extraction and selection from acoustic emission signals with an application in grinding wheel condition monitoring.
T. Warren LiaoPublished in: Eng. Appl. Artif. Intell. (2010)
Keyphrases
- acoustic emission
- condition monitoring
- feature extraction and selection
- pattern recognition
- fault detection
- fault diagnosis
- feature set
- nuclear power plant
- power transformers
- tool wear
- feature extraction
- decision making
- intelligent systems
- face recognition
- vibration signal
- artificial intelligence
- classification accuracy
- data sets