Bibliometric Database for Improvement Methods of Wooden Musical Instruments

This study establishes a bibliometric database for wooden instrument improvement methods, integrating multidisciplinary research achievements through a systematic literature review approach to reveal the comprehensive research landscape of wood acoustic performance enhancement. The database sources 1,983 original articles from four authoritative platforms, including Web of Science and Scopus, and employs a PRISMA-compliant four-tier screening process to ultimately include 51 high-quality publications. Its data architecture spans three dimensions—metadata (title/author/year/journal), research content (experimental methods/core themes), and influencing factors (theoretical mechanisms/structural parameters)—leveraging Zotero-VOSviewer-CiteSpace analytical tools for quantitative analysis. It specifically focuses on the acoustic vibration parameter system of wood, encompassing seven key indicators such as specific dynamic elastic modulus and acoustic radiation quality constant, while integrating interdisciplinary improvement methods including physical treatments (thermal aging), chemical modifications (acetylation), and biotechnologies (microbial fermentation). Validated by 90.2% coding consistency and 0.98 reliability, the database precisely maps the field’s evolutionary trajectory from traditional craftsmanship to AI simulation and sustainable material development. It provides data-driven support to resolve the conflict between scarce premium wood resources and acoustic quality enhancement, advancing the digital and ecological transformation of wood-based instrument manufacturing.

本研究构建了木质乐器改良方法文献计量数据库（bibliometric database），通过系统文献综述（systematic literature review）方法整合多学科研究成果，以揭示木材声学性能提升领域的完整研究图景。该数据库从Web of Science、Scopus等4个权威平台收录1983篇原创论文，并遵循系统评价与荟萃分析优先报告条目（PRISMA）标准开展四级筛选流程，最终纳入51篇高质量文献。其数据架构涵盖三大维度——元数据（metadata，标题/作者/发表年份/期刊）、研究内容（实验方法/核心主题）与影响因素（理论机制/结构参数），并依托Zotero、VOSviewer、CiteSpace分析工具开展定量分析。该库专门聚焦木材声学振动参数体系，涵盖比动态弹性模量（specific dynamic elastic modulus）、声辐射品质常数（acoustic radiation quality constant）等7项关键指标，同时整合了物理处理（physical treatments，热老化）、化学改性（chemical modifications，乙酰化）、生物技术（biotechnologies，微生物发酵）等跨学科改良方法。经90.2%的编码一致性（coding consistency）与0.98的信度（reliability）检验验证，该数据库精准勾勒出该领域从传统工艺到AI模拟、可持续材料研发的演进轨迹。其可为破解优质木材资源稀缺与声学性能提升之间的矛盾提供数据支撑，推动木质乐器制造业的数字化与生态化转型。