利用计算效率高的多体模型捕捉通过坐姿人体的振动传播

IF 2.6 2区 工程技术 Q2 MECHANICS Multibody System Dynamics Pub Date : 2024-09-06 DOI:10.1007/s11044-024-10025-1
Raj Desai, Georgios Papaioannou, Riender Happee
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引用次数: 0

摘要

通过坐姿人体传播振动的现有模型主要是二维模型,侧重于中矢状面和面内激励。然而,当人体受到中冠状面的振动时,这些模型就会受到限制。三维(3D)人体模型主要用于冲击分析。最近,我们发现这种三维主动人体模型也可以预测振动传播。然而,现有的三维人体模型因其复杂性而需要过多的计算时间。为了有效分析运动舒适性,本研究提出了一种三维计算效率高的人体模型(EHM),其运行速度比实时模型更快,可用于实时车辆和座椅运动控制,以提高舒适性。EHM 的开发考虑了各种身体节段和关节自由度组合,并与多体(MB)和有限元(FE)座椅顺应性模型相互作用。根据不同姿势(直立/倾斜)和靠背支撑(低/高)条件下与频率相关的增益响应实验,通过优化过程估算姿势稳定参数。该模型结合了两种姿势控制机制:1)关节角度控制,利用 PID 控制器捕捉每个自由度的反射和内在稳定,包括消除漂移的集成;2)头部空间控制,最大限度地减少头部的三维旋转。使用可变形有限元和多体接触模型对与顺应性座椅的交互进行建模。结果表明,对座椅和人体的压缩和剪切变形进行建模非常重要。传统的粘滑多体接触无法再现座椅与人体之间的振动传递。这项研究结合了高效的人体建模原理、创新的姿势适应技术和先进的座椅接触策略,为预测和优化运动舒适性奠定了坚实的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Vibration transmission through the seated human body captured with a computationally efficient multibody model

Existing models of vibration transmission through the seated human body are primarily two-dimensional, focusing on the mid-sagittal plane and in-plane excitation. However, these models have limitations when the human body is subjected to vibrations in the mid-coronal plane. Three-dimensional (3D) human models have been primarily developed for impact analysis. Recently, we showed that such a 3D active human model can also predict vibration transmission. However, existing 3D body models suffer from excessive computational time requirements due to their complexity. To effectively analyze motion comfort, this research presents a 3D computationally efficient human model (EHM), running faster than real-time, with scope for real-time vehicle and seat motion control to enhance comfort. The EHM is developed by considering various combinations of body segments and joint degrees of freedom, interacting with multibody (MB) and finite element (FE) seat compliance models. Postural stabilization parameters are estimated using an optimization process based on experimental frequency-dependent gain responses for different postures (erect/slouched) and backrest support (low/high) conditions. The model combines two postural control mechanisms: 1) joint angle control capturing reflexive and intrinsic stabilization for each degree of freedom with PID controllers, including integration to eliminate drift, and 2) head-in-space control minimizing 3D head rotation. Interaction with a compliant seat was modeled using deformable finite elements and multibody contact models. Results showed the importance of modeling both compressive and shear deformation of the seat and the human body. Traditional stick-slip multibody contact failed to reproduce seat-to-human vibration transmission. Combining efficient body modeling principles, innovative postural adaptation techniques, and advanced seat contact strategies, this study lays a robust foundation for predicting and optimizing motion comfort.

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来源期刊
CiteScore
6.00
自引率
17.60%
发文量
46
审稿时长
12 months
期刊介绍: The journal Multibody System Dynamics treats theoretical and computational methods in rigid and flexible multibody systems, their application, and the experimental procedures used to validate the theoretical foundations. The research reported addresses computational and experimental aspects and their application to classical and emerging fields in science and technology. Both development and application aspects of multibody dynamics are relevant, in particular in the fields of control, optimization, real-time simulation, parallel computation, workspace and path planning, reliability, and durability. The journal also publishes articles covering application fields such as vehicle dynamics, aerospace technology, robotics and mechatronics, machine dynamics, crashworthiness, biomechanics, artificial intelligence, and system identification if they involve or contribute to the field of Multibody System Dynamics.
期刊最新文献
Development of an identification method for the minimal set of inertial parameters of a multibody system Vibration transmission through the seated human body captured with a computationally efficient multibody model Data-driven inverse dynamics modeling using neural-networks and regression-based techniques Load torque estimation for cable failure detection in cable-driven parallel robots: a machine learning approach Mutual information-based feature selection for inverse mapping parameter updating of dynamical systems
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