In this paper we present the Physics-Aware Deep-NMF (PAD-NMF) algorithm and we apply it to hit detection in mechanical systems from audio mixtures. The algorithm accurately extracts the acoustic emission made by the physical source to be monitored, to be properly used in engineering analysis, like e.g. the hit detection here considered. This is mainly a source separation problem where sources have a precise physical meaning, that should be retained by the processing algorithm. For this reason we call this algorithm a Physics-aware soft-sensor. We give a detailed description of the algorithm and show its results on a general application with critical signal-to-noise ratios, where the noise is a mixture of random and deterministic acoustic sources.

Hit detection in audio mixtures by means of a physics-aware Deep-NMF algorithm

Chinellato E.;Marcuzzi F.
2025

Abstract

In this paper we present the Physics-Aware Deep-NMF (PAD-NMF) algorithm and we apply it to hit detection in mechanical systems from audio mixtures. The algorithm accurately extracts the acoustic emission made by the physical source to be monitored, to be properly used in engineering analysis, like e.g. the hit detection here considered. This is mainly a source separation problem where sources have a precise physical meaning, that should be retained by the processing algorithm. For this reason we call this algorithm a Physics-aware soft-sensor. We give a detailed description of the algorithm and show its results on a general application with critical signal-to-noise ratios, where the noise is a mixture of random and deterministic acoustic sources.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3540614
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