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Enhancement of decomposed spectral coherence using sparse nonnegative matrix factorization

机译：利用稀疏非负矩阵分解提高分解光谱相干性

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摘要

Integration of the spectral coherence over the domain of spectral frequency is one popular way for reaching the envelope spectrum which is an indispensable tool for the fault diagnosis of rotating machineries. Envelope spectrum can be enhanced by introducing a decomposition of spectral coherence with the aid of nonnegative matrix factorization frequently exploited for the data clustering. Based on this regime, the present study aims to deal with further improvement of the envelope spectrum by taking two major considerations. First, it is to impose a sparsity constraint to the minimization problem treated in the standard NMF, eventually allowing a sparse representation of the envelope spectrum. By taking advantage of a randomness of NMF solution, the second is to establish how to correctly choose the number of clusters, a prerequisite for starting the NMF algorithm. Finally, the suggested method is verified throughout a synthetic data and experimental measurement from propeller cavitation.
机译：通过频谱频率领域的光谱相干谱的集成是用于到达信封谱的一种流行方式，这是一种用于旋转机械的故障诊断的不可缺少的工具。通过借助于对数据聚类经常利用的非负矩阵分组引入光谱相干性分解，可以提高信封频谱。基于这一制度，本研究旨在通过考虑两项重大考虑来处理包络谱的进一步改善。首先，将稀疏限制施加到标准NMF中处理的最小化问题，最终允许包络光谱的稀疏表示。通过利用NMF解决方案的随机性，第二个是建立如何正确选择群集数量，启动NMF算法的先决条件。最后，在整个合成数据和螺旋桨空化的实验测量中验证了建议的方法。

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