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

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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Publication Details

Journal
Mechanical Systems and Signal Processing
Published
2024-11-26
DOI
https://doi.org/10.1016/j.ymssp.2024.112162
Citations
6
Primary Topic
Music and Audio Processing
Type
article
Field-Weighted Citation Impact
2.10
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article

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

Fabio Marcuzzi, Erik Chinellato
6 citations
Mechanical Systems and Signal Processing
Music and Audio Processing
2.10
article

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

Fabio Marcuzzi, Erik Chinellato
article en
6 citations

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.

Mechanical Systems and Signal ProcessingVol. 224
University of Padua (IT)
Openalex Percentile: Top 11%
Music and Audio Processing
2.10
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