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.

中文翻译：

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通过物理感知 Deep-NMF 算法在音频混合中进行命中检测


在本文中，我们提出了物理感知 Deep-NMF （PAD-NMF） 算法，并将其应用于机械系统中音频混合的命中检测。该算法准确地提取了要监测的物理源产生的声发射，以正确用于工程分析，例如这里考虑的命中检测。这主要是一个源分离问题，其中源具有精确的物理含义，应该由处理算法保留。因此，我们将此算法称为物理感知软传感器。我们详细描述了该算法，并展示了它在具有临界信噪比的一般应用中的结果，其中噪声是随机和确定性声源的混合物。