Anomaly Detection by Reconstructing Features from Subsampled Audio Signals

摘要

We aim to reduce the cost of sound monitoring for maintain machinery by reducing the sampling rate, i.e., sub-Nyquist sampling. Monitoring based on sub-Nyquist sampling requires two sub-systems: a sub-system on-site for sampling machinery sounds at a low rate and a sub-system off-site for detecting anomalies from the subsampled signal. This paper proposes a feature reconstruction method for enabling anomaly detection from the subsampled signal.