An Autoencoder-Based Approach for Anomaly Detection of Machining Processes Using Acoustic Emission Signals.
Antonio NappaJuan Luis Ferrando ChacónIzar AzpirozPedro José ArrazolaPublished in: EANN (2024)
Keyphrases
- acoustic emission
- anomaly detection
- machining processes
- tool wear
- condition monitoring
- intrusion detection
- detecting anomalies
- anomalous behavior
- network traffic
- network intrusion detection
- manufacturing processes
- real time control
- network anomaly detection
- detect anomalies
- multi sensor
- parameter optimization
- intrusion detection system
- one class support vector machines
- negative selection algorithm
- fault detection
- fault diagnosis
- unsupervised learning
- genetic algorithm
- feature vectors