数字标准人的研究现状、关键技术与未来展望

方卫宁; 张运红; 司峰; 方程乐; 侯博文; 胡胜建

doi:10.19554/j.cnki.1001-3563.2026.16.001

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包装工程（设计栏目） ›› 2026, Vol. 47 ›› Issue (16) : 1-21. DOI: 10.19554/j.cnki.1001-3563.2026.16.001

专题：复杂装备场景下的数字人关键技术及应用

数字标准人的研究现状、关键技术与未来展望

方卫宁^1a,b, 张运红^2,*, 司峰², 方程乐^1a,b, 侯博文³, 胡胜建^1a,c

作者信息 +

Research Status, Key Technologies and Future Prospects of the Standard Digital Human Model

FANG Weining^1a,b, ZHANG Yunhong^2,*, SI Feng², FANG Chengle^1a,b, HOU Bowen³, HU Shengjian^1a,c

Author information +

文章历史 +

摘要

目的数字标准人是工业设计与人机工效评价的重要基础工具。国内相关设计工作大多沿用依托欧美人体数据库构建的模型与软件,存在人群适配偏差与数据不一致问题。研究明确面向中国人形态特征的数字标准人关键技术方向,为工效数字化设计自主可控提供参考。方法采用叙述性综述与概念分析,以国内外文献及ISO/GB等标准为来源,纳入建模方法、人群测量数据、感知与生物力学模型及标准文献,由数字标准人的本质属性出发归纳关键技术。结果提出统计代表性、量值可溯源性与场景内工程评价能力三项本质属性,据此厘清其与数字人、人体数字孪生的边界,推导出允差确定与检测校准误差控制、关节功能中心定位与形态-功能建模、感知分层建模与验证三项关键技术;其误差由测量、抽样、模型逼近与场景迁移四层构成,并受五类结构性权衡制约。结论构建面向中国人群的数字标准人的参数化模型族、任务导向的最小充分参数集、“人群基准-场景修正”双层结构、感知量约定参考体系与可审计的人工智能协同机制。

Abstract

The standard digital human model (SDHM) is a fundamental tool for industrial design and human-machine ergonomic evaluation. Ergonomic design in China still relies largely on models and software built upon Western anthropometric data, giving rise to population-adaptation bias and data inconsistency. The work aims to identify the key technical directions of an SDHM oriented to the characteristics of the Chinese population, so as to provide a reference for independent and controllable ergonomic digital design. A narrative review combined with conceptual analysis was adopted. Drawing on Chinese and international literature together with ISO and GB standards, the review covered modeling methods, population measurement data, perception and biomechanical models, and standard literature and the key technologies were then derived from the essential attributes of the SDHM. Three essential attributes were proposed, including statistical representativeness, metrological traceability, and engineering evaluation capability within stated scenario boundaries, on the basis of which the SDHM was distinguished from conventional digital human models and human digital twins. Three key technologies were derived accordingly, including tolerance determination and calibration error control, functional joint-center localization and morphology-function modeling and hierarchical modeling and validation of perception. The error of an SDHM comprised four layers, including measurement, sampling, model approximation, and scenario transfer and its development was constrained by five structural trade-offs. Building an SDHM for the Chinese population depends less on geometric fidelity than on establishing a standardized model system: a parametric model family to ensure population representativeness, a task-oriented minimal sufficient parameter set, a two-layer structure separating the "population benchmark from scenario corrections", a conventional reference system for perceptual quantities, and an auditable coordination mechanism between artificial intelligence and the standard system.

导出引用1

方卫宁, 张运红, 司峰, 方程乐, 侯博文, 胡胜建. 数字标准人的研究现状、关键技术与未来展望[J]. 包装工程. 2026, 47(16): 1-21 https://doi.org/10.19554/j.cnki.1001-3563.2026.16.001

FANG Weining, ZHANG Yunhong, SI Feng, FANG Chengle, HOU Bowen, HU Shengjian. Research Status, Key Technologies and Future Prospects of the Standard Digital Human Model[J]. Packaging Engineering. 2026, 47(16): 1-21 https://doi.org/10.19554/j.cnki.1001-3563.2026.16.001

中图分类号： TB482

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