Musical Acoustics Lab at the Violin Museum of Cremona, DEIB-Politecnico di Milano, Cremona Campus, Cremona, Italy.
Department of Electrical Engineering, Faculty of Physical and Mathematical Sciences, University of Chile, Santiago, Chile.
Sci Rep. 2021 May 4;11(1):9455. doi: 10.1038/s41598-021-88931-z.
Of all the characteristics of a violin, those that concern its shape are probably the most important ones, as the violin maker has complete control over them. Contemporary violin making, however, is still based more on tradition than understanding, and a definitive scientific study of the specific relations that exist between shape and vibrational properties is yet to come and sorely missed. In this article, using standard statistical learning tools, we show that the modal frequencies of violin tops can, in fact, be predicted from geometric parameters, and that artificial intelligence can be successfully applied to traditional violin making. We also study how modal frequencies vary with the thicknesses of the plate (a process often referred to as plate tuning) and discuss the complexity of this dependency. Finally, we propose a predictive tool for plate tuning, which takes into account material and geometric parameters.
在小提琴的所有特征中，与形状相关的特征可能是最重要的，因为制琴师可以完全控制这些特征。然而，现代制琴仍然更多地基于传统而非理解，对于形状和振动特性之间存在的具体关系的明确科学研究尚未出现，而且这方面的研究非常欠缺。在本文中，我们使用标准的统计学习工具表明，小提琴面板的模态频率实际上可以从几何参数中预测，并且人工智能可以成功地应用于传统的小提琴制作。我们还研究了模态频率如何随板厚的变化而变化（这个过程通常称为板调谐），并讨论了这种依赖性的复杂性。最后，我们提出了一种考虑材料和几何参数的板调谐预测工具。
