Christian Gawron

Spectrogram-Based CNN Autoencoder for One-Class Anomaly Detection in Machining Vibration Signals

This work presents a one-class anomaly detection framework for vibration-based condition monitoring in machining processes using a convolutional neural network autoencoder. Three-axis vibration signals acquired during industrial broaching are transformed into time–frequency spectrograms and combined into a compact thre...