Valentino Peluso

Self-Supervised Anomaly Detection for Industrial Machines With Sensor Distance Classification

A novel self-supervised strategy for effective single-machine training based on classifying the distance between the monitored machine and each microphone sensor of a multi-channel recording system is introduced, providing a cost-efficient and privacy-preserving alternative while delivering competitive detection performance.