Audio anomaly detection on rotating machinery using image signal processing

This paper addresses the problem of anomaly detection on rotating machinery in industrial environments using single channel audio signals. The proposed algorithm is based on image processing feature analysis obtained from the image representation of the Short-time Fourier Transform of reference and degraded audio signals. In order to assess the potential of the algorithm, a 8 signals database is recorded. The proposed algorithm is able to separate signals of machinery normal behavior from signals of machinery anomalous behavior with 100% hit rate using the recorded database.