Model-Based Analysis and Design Optimization of Music Instruments

基于模型的乐器分析与设计优化

• 批准号: RGPIN-2020-04874
• 负责人: Scavone, Gary
• 金额: $ 2.84万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=716936
• 关键词: Model; Based; Analysis; Design; Optimization

The long--term goal of this research program is to improve our scientific understanding of the aeroacoustic and mechanical properties of music instruments that can aid in their design, manufacture, pedagogy and sound synthesis. Musical instruments have been developed over centuries through empirical methods and have reached very high levels of refinement. That said, there remain various problems experienced by makers, manufacturers and players for which solutions can be found. Instrument designs often involve compromises. For example, a modification made to improve intonation may inadvertently produce a less consistent timbre. Computer modeling methods can be applied to find optimized or tailored solutions. Our focus is primarily on music instruments, though the research methods, results and skills acquired in conducting this research will be applicable in a wide range of technological, multimedia, and acoustical engineering fields. The first specific objective of this research proposal is to better understand the link between geometric, aeroacoustic and playing parameters of woodwind instrument mouthpieces using measurements and computer modeling. This component of the proposal is a continuation of a previous objective, building on previous achievements. We will make use of Finite Element (FE) and aeroacoustic modeling to characterize the tone quality (acoustic) and playability (fluid-structure-interaction) properties. This research will also involve measurements using a hot-wire anemometer and pressure probes with a mechanical woodwind player system to assess the fluid flow characteristics and inform the 3D aeroacoustic modeling. The second objective of the proposal is to develop computer modeling approaches for the design of marimba bars that can optimize for tuning, minimize undesirable cross-mode coupling, and support explorations with composite materials as a replacement for endangered rosewood. The approach will combine FE and optimization methods, with extensions to account for sound radiation, coupling with marimba resonator pipes, and auralization. We will collaborate with specialists in the design and fabrication of natural fiber composite materials to seek new materials that can replace rosewood while maintaining the same timbral quality as traditional marimbas. The third objective of the proposal will involve the design and development of algorithmic systems that can learn to imitate the musical expressivity of human musicians when performing with virtual physics-based synthesis models or with a mechanical player system. The approach will make use of methods from artificial intelligence and machine learning, as well as robotics and music pedagogy. Results of this research will improve current efforts in the design / analysis / evaluation of music instruments, inform teachers and students about proper or more efficient ways of playing their instruments, and also have application in commercial acoustical engineering contexts.

这项研究计划的长期目标是提高我们对乐器的航空声学和机械特性的科学理解，这些特性可以帮助乐器的设计，制造，教学和声音合成。乐器已经通过经验方法开发了几个世纪，并达到了非常高的精细化水平。也就是说，制造商、制造商和演奏者仍然面临各种各样的问题，可以找到解决方案。乐器设计往往涉及妥协。例如，为了改善语调而进行的修改可能会无意中产生不太一致的音色。计算机建模方法可用于找到优化或定制的解决方案。我们的重点主要是在乐器，虽然在进行这项研究的研究方法，成果和获得的技能将适用于广泛的技术，多媒体和声学工程领域。 本研究建议的第一个具体目标是使用测量和计算机建模更好地了解木管乐器吹嘴的几何，航空声学和演奏参数之间的联系。建议中的这一部分是在以往成就的基础上延续以往的目标。我们将利用有限元（FE）和航空声学建模来表征音质（声学）和可玩性（流体-结构-相互作用）特性。这项研究还将涉及使用热线风速计和压力探头与机械木管演奏系统进行测量，以评估流体流动特性并为3D航空声学建模提供信息。 该提案的第二个目标是为马林巴琴杆的设计开发计算机建模方法，该方法可以优化调谐，最大限度地减少不希望的交叉模式耦合，并支持复合材料作为濒危红木替代品的探索。该方法将结合联合收割机和优化方法，并扩展以考虑声音辐射、与马林巴琴共鸣管耦合和可听化。我们将与天然纤维复合材料的设计和制造专家合作，寻求可以取代红木的新材料，同时保持与传统木琴相同的音色质量。 该提案的第三个目标将涉及算法系统的设计和开发，该系统可以学习模仿人类音乐家在使用基于虚拟物理的合成模型或机械播放器系统进行表演时的音乐表现力。该方法将利用人工智能和机器学习的方法，以及机器人和音乐教学法。 本研究的结果将改善目前的努力，在设计/分析/评估的乐器，告知教师和学生正确或更有效的方式演奏他们的乐器，也有应用在商业声学工程背景。