Article(id=1225751354593948026, tenantId=1146029695717560320, journalId=1225147924628267009, issueId=1225751351125263080, articleNumber=null, orderNo=null, doi=10.16385/j.cnki.issn.1004-4523.202312005, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1701360000000, receivedDateStr=2023-12-01, revisedDate=1705248000000, revisedDateStr=2024-01-15, acceptedDate=null, acceptedDateStr=null, onlineDate=1770171496293, onlineDateStr=2026-02-04, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1770171496293, onlineIssueDateStr=2026-02-04, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1770171496293, creator=13701087609, updateTime=1770171496293, updator=13701087609, issue=Issue{id=1225751351125263080, tenantId=1146029695717560320, journalId=1225147924628267009, year='2025', volume='38', issue='10', pageStart='2205', pageEnd='2462', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1770171495466, creator=13701087609, updateTime=1774228911890, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1242769389133611807, tenantId=1146029695717560320, journalId=1225147924628267009, issueId=1225751351125263080, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1242769389133611808, tenantId=1146029695717560320, journalId=1225147924628267009, issueId=1225751351125263080, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=2205, endPage=2213, ext={EN=ArticleExt(id=1225751354883355004, articleId=1225751354593948026, tenantId=1146029695717560320, journalId=1225147924628267009, language=EN, title=Finite element modeling of seat transmissibility of the human-seat system with the variation in excitation characteristics, columnId=null, journalTitle=Journal of Vibration Engineering, columnName=null, runingTitle=null, highlight=null, articleAbstract=

The quantitative analysis of the effect of low-frequency vibrations on the sitting comfort has been a pivotal focus in the field of transportation engineering. In this study, the transmission of vibration through the human-seat system with different excitation conditions is predicted and analyzed using the finite element modeling. Individual finite element models for the human body and the seat, along with their respective contact properties, are constructed and integrated into an overall finite element model of the human-seat system. The model parameters are validated utilizing experimental data from static body pressure distribution at cushion and backrest locations, as well as the measured seat transmissibility obtained with the vertical excitation. The results indicate the finite element model, validated through the calibration, demonstrates a good fit with experimental data for the seat transmissibility under the fore-and-aft excitation. However, there is a deviation in the amplitude at the resonance frequency. Additionally, the model predicts that the resonance frequency of the seat transmissibility decreases with an increase in the excitation amplitude, and this trend aligns well with experimental results, particularly under the vertical excitation. The constructed model accurately reflects the dynamic response of the human-seat system with different conditions. It serves as a valuable reference for the seat design.

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低频振动对驾乘舒适性的影响一直是NVH领域的研究重点之一,本文采用有限元建模方法预测和分析不同激励环境下的人体‑座椅系统振动传递特性,通过构建人体、座椅有限元模型以及根据两者的接触属性建立人体‑座椅整体有限元简化模型,并分别结合坐垫及靠背处静态体压分布试验数据和垂向激励下的座椅频响函数试验结果校核模型参数。结果表明,校核后的整体系统有限元模型在水平前后向激励下预测的座椅频响函数与试验数据吻合度较好,但在共振频率处的响应幅值存在偏差。同时,模型预测得出的座椅频响函数共振频率随激励幅值增加而降低,且与试验测试结果变化趋势基本一致,所构建的模型能够较为准确地反映不同工况下的人体‑座椅系统振动响应,可为座椅优化设计提供有益参考。

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张筱璐(1984—),男,博士,副教授。E-mail:
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The stiffness and damping of joints used in the model

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身体关节刚度/(N‧m‧rad-1阻尼/(N‧m‧s‧rad-1
胸关节24209.8
腰关节208027.2
髋关节53621.3
膝关节280280.6
), ArticleFig(id=1225751368594534419, tenantId=1146029695717560320, journalId=1225147924628267009, articleId=1225751354593948026, language=CN, label=表1, caption=

坐姿人体模型的关节刚度与阻尼

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身体关节刚度/(N‧m‧rad-1阻尼/(N‧m‧s‧rad-1
胸关节24209.8
腰关节208027.2
髋关节53621.3
膝关节280280.6
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垂向及水平前后向激励下座椅频响函数的有限元建模研究
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张筱璐 1, 2 , 王新伟 1 , 余培锦 1 , 宋希晨 1
振动工程学报 | 2025,38(10): 2205-2213
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振动工程学报 | 2025, 38(10): 2205-2213
垂向及水平前后向激励下座椅频响函数的有限元建模研究
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张筱璐1, 2 , 王新伟1, 余培锦1, 宋希晨1
作者信息
  • 1.北京工业大学机械与能源工程学院,北京 100124;
  • 2.北京工业大学汽车结构部件先进制造技术教育部工程研究中心,北京 100124

通讯作者:

张筱璐(1984—),男,博士,副教授。E-mail:
Finite element modeling of seat transmissibility of the human-seat system with the variation in excitation characteristics
Xiaolu ZHANG1, 2 , Xinwei WANG1, Peijin YU1, Xichen SONG1
Affiliations
  • 1.College of Mechanical & Energy Engineering, Beijing University of Technology, Beijing 100124, China
  • 2.Engineering Research Center of Advanced Manufacturing Technology for Automotive Components, Ministry of Education, Beijing University of Technology, Beijing 100124, China
doi: 10.16385/j.cnki.issn.1004-4523.202312005
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低频振动对驾乘舒适性的影响一直是NVH领域的研究重点之一,本文采用有限元建模方法预测和分析不同激励环境下的人体‑座椅系统振动传递特性,通过构建人体、座椅有限元模型以及根据两者的接触属性建立人体‑座椅整体有限元简化模型,并分别结合坐垫及靠背处静态体压分布试验数据和垂向激励下的座椅频响函数试验结果校核模型参数。结果表明,校核后的整体系统有限元模型在水平前后向激励下预测的座椅频响函数与试验数据吻合度较好,但在共振频率处的响应幅值存在偏差。同时,模型预测得出的座椅频响函数共振频率随激励幅值增加而降低,且与试验测试结果变化趋势基本一致,所构建的模型能够较为准确地反映不同工况下的人体‑座椅系统振动响应,可为座椅优化设计提供有益参考。

人‑椅系统  /  座椅频响函数  /  有限元模型  /  振动幅值  /  非线性

The quantitative analysis of the effect of low-frequency vibrations on the sitting comfort has been a pivotal focus in the field of transportation engineering. In this study, the transmission of vibration through the human-seat system with different excitation conditions is predicted and analyzed using the finite element modeling. Individual finite element models for the human body and the seat, along with their respective contact properties, are constructed and integrated into an overall finite element model of the human-seat system. The model parameters are validated utilizing experimental data from static body pressure distribution at cushion and backrest locations, as well as the measured seat transmissibility obtained with the vertical excitation. The results indicate the finite element model, validated through the calibration, demonstrates a good fit with experimental data for the seat transmissibility under the fore-and-aft excitation. However, there is a deviation in the amplitude at the resonance frequency. Additionally, the model predicts that the resonance frequency of the seat transmissibility decreases with an increase in the excitation amplitude, and this trend aligns well with experimental results, particularly under the vertical excitation. The constructed model accurately reflects the dynamic response of the human-seat system with different conditions. It serves as a valuable reference for the seat design.

human-seat system  /  seat transmissibility  /  finite element modeling  /  excitation amplitude  /  non-linearity
张筱璐, 王新伟, 余培锦, 宋希晨. 垂向及水平前后向激励下座椅频响函数的有限元建模研究. 振动工程学报, 2025 , 38 (10) : 2205 -2213 . DOI: 10.16385/j.cnki.issn.1004-4523.202312005
Xiaolu ZHANG, Xinwei WANG, Peijin YU, Xichen SONG. Finite element modeling of seat transmissibility of the human-seat system with the variation in excitation characteristics[J]. Journal of Vibration Engineering, 2025 , 38 (10) : 2205 -2213 . DOI: 10.16385/j.cnki.issn.1004-4523.202312005
交通运输中的振动环境会对驾乘人员舒适性产生影响并引发健康问题,汽车运行环境中的振动激励较为复杂,其中垂向与水平前后向激励对驾乘舒适性影响较大[12]。座椅频响函数(seat transmissibility) 常用于描述振动激励经过座椅结构传递至坐姿人体的总体系统动态响应,且座椅动力学因素和人体生物动力学因素均对座椅频响函数具有显著影响[3]
为简化目标对象,研究人员首先研究了垂向或水平前后向激励下刚性座椅上坐姿人体的动态响应特征,常以视在质量(apparent mass)为量化手段。在垂向激励下,坐垫处的垂向同轴视在质量峰值频率在4~6 Hz范围内,且存在明显的非线性特性,即视在质量的峰值频率随激励幅值增加而降低[4]。在水平前后向激励下,坐垫处的水平前后向同轴视在质量峰值频率在1~3 Hz范围内,且峰值频率随激励幅值的增加也呈下降趋势[5]。人体在水平前后向激励下的主共振模态主要是由腰椎和下胸椎的弯曲,以及臀部和大腿处软组织的剪切变形引起[6],这与垂向激励下的共振模态可能存在较大差异。
上述在试验条件下刚性座椅上测得的视在质量仅反映了人体对振动输入的响应特性,难以捕捉加装有各种弹性减振材料的真实座椅与人体的耦合效应[7],人‑椅总体系统的振动传递特性也受座椅动态特性的影响[8]。增加泡沫厚度会显著提高垂向同轴和水平前后向交叉轴座椅频响函数的峰值传递率[9],座椅频响函数的峰值频率也会随座椅倾斜角度的增加而显著上升[3]。硬度较低的座椅易导致驾乘人员神经疲劳,而硬度较高的座椅更易支撑人体,人体疲劳感相对较低[10]。因此,在研究不同激励特征下人‑椅系统的振动传递特性时,应结合人体生物动力学与座椅动力学两方面因素综合衡量。
由于人‑椅系统振动试验研究耗费较大,研究人员尝试依托已有试验研究成果开展模型构建和优化,主要包括集中参数模型(lumped parameter model)、多体动力模型(multi‑body dynamic model)和有限元模型(finite element model)等。集中参数模型是通过质量块、阻尼、弹簧等机械结构建立的特定系统,常用于描述坐姿人体的生物动力学响应[1112]。相比集中参数模型,多体动力学模型在模拟人体俯仰运动方面存在较大优势,便于进一步探究系统的局部响应和正交轴响应[1316]。然而,由于集中参数模型和多体动力学模型对接触界面进行了较大程度地简化,因此在反映人‑椅界面处的动态交互作用方面存在限制,如当坐姿人体与座椅坐垫充分接触时,人体坐骨神经位置由外向内的接触受力变化难以通过此类模型实现。
有限元模型在模拟复杂接触表面的压力和变形进而更准确地预测系统动态特性方面具有明显优势[1719]。研究发现,在垂向激励下,增加座椅模型刚度会导致人体腰间盘在垂向与水平前后向两个方向上的响应频率提高[20],适当降低坐垫处泡沫模型的硬度参数可以有效提高人体的静态舒适性指数[21]。然而在当前有限元模型研究中,缺乏对不同激励幅值对于座椅频响函数预测效果的影响探究。在不同激励方向或激励幅值条件下,系统特性可能发生变化并导致座椅频响函数存在差异,增加了模型预测的难度。因此,需要进一步探究不同振动环境下的激励特征对人‑椅系统有限元模型预测性能及其可靠性的影响,以增强模型在实际驾乘振动环境下的适用性。
为探索有限元建模方法在不同激励工况下对人‑椅系统振动传递特性的预测性能,本文基于试验研究构建可同时预测垂向及水平前后向激励下座椅地板到坐垫及靠背处同轴座椅频响函数的人‑椅系统有限元模型,并进一步预测不同激励幅值下座椅频响函数的变化规律,为改善驾乘舒适性提供有益的参考。
在本研究中,六自由度振动平台上固定有座椅,刚性座椅的坐垫和靠背中心位置处分别固定开孔聚氨酯泡沫,泡沫样本尺寸为450 mm×450 mm×90 mm(如图1所示)。垂向激励、水平前后向激励的激励幅值分别确定为0.2、0.4和0.8 m/s2。试验激励信号均为随机限宽白噪声振动信号,激励信号的持续时间为60 s。底板处加速度由PCB三轴加速度计测得,坐垫及靠背处加速度由采集灵敏度为100 mV/g的SIT‑pad加速度传感器测得。12名男性参与试验,且均身体健康,无骨骼、肌肉疾病。试验过程中要求参试人员保持如图1(b)所示姿态,眼睛目视前方。
本文选择座椅频响函数作为人‑椅系统振动传递特性的量化指标,其可由人体与座椅接触面处的振动响应与座椅底板输入激励计算确定:
T(f)=Gio(f)Gii(f)
式中,Giof)为输出与输入加速度的互功率谱密度; Giif)为输入加速度的自功率谱密度;Tf)为座椅频响函数。
本文涉及4种座椅频响函数,具体如下:
①坐垫处垂向同轴频响函数:由底板处垂向加速度输入信号azf和坐垫处垂向加速度输出信号asz计算得到。
②靠背处垂向同轴频响函数:由底板处垂向加速度输入信号azf和靠背处垂向加速度输出信号abz计算得到。
③坐垫处水平前后向同轴频响函数:由底板处水平前后向加速度输入信号axf和坐垫处水平前后向加速度输出信号asx计算得到。
④靠背处水平前后向同轴频响函数:由底板处水平前后向加速度输入信号axf和靠背处水平前后向加速度输出信号abx计算得到。
在不同垂向激励幅值条件下,坐垫处和靠背处垂向同轴座椅频响函数中值如图2所示。当激励幅值从0.2 m/s2递增至0.8 m/s2时,坐垫处垂向同轴频响函数的共振处幅值和共振频率均逐渐减小,靠背处垂向同轴频响函数变化趋势与坐垫处基本一致。垂向激励幅值引起的座椅频响函数非线性特性与坐姿人体视在质量研究结果类似,这是由于随着垂向激励幅值增加,人体的肌肉逐渐松弛,人体刚度因此减小。同时,泡沫的动刚度亦会随激励幅值的增加而逐渐减小。因此,在垂向激励增大时,人‑椅总体系统的刚度会呈现下降趋势,进而导致座椅频响函数的共振频率降低。
在不同水平前后向激励幅值条件下,坐垫和靠背处水平前后向同轴频响函数中值如图3所示。随着水平前后向激励幅值(r.m.s.)从0.2 m/s2递增至0.8 m/s2,水平前后向同轴频响函数的共振频率处幅值与共振频率均呈下降趋势,人‑椅系统同样表现出明显的“软化”效应。由于坐姿人体水平前后向振动模态主要与人体腰椎、下胸椎的弯曲形变和坐骨神经处组织的剪切形变相关[3],人‑椅系统动态特性可能也与上述运动相关,其刚度因系统运动特性的变化而减小,导致座椅频响函数共振频率随水平前后向激励幅值增大向低频偏移。
分析发现,在不同垂向激励幅值条件下,座椅频响函数的共振频率在4.75~5 Hz范围内变化,在不同水平前后向激励幅值条件下,其共振频率在3.75~4.25 Hz范围内变化(见图23)。座椅频响函数共振频率的偏移表明人‑椅系统的振动响应对不同激励条件具有较高敏感性。在人‑椅系统有限元模型构建过程中,需引入适用的非线性材料模型和接触模型,以准确描述其在不同激励工况下的振动响应。
本文基于Poser软件结合人体解剖学和人体测量学数据构建身高为172.5 cm的标准中国男性直立坐姿人体简化几何模型,该模型主要由头‑颈部、胸‑肩部、上臂‑下臂部、腹部、大腿‑臀部以及小腿‑脚部六部分组成。其中,人体躯干主体为胸部、腹部以及臀部,人体活动肢体均限制于主体躯干外侧,模型中的人体骨骼以及人体表面多为不规则曲面,因此在划分人体网格时重点选择四面体单元,而较为规则的六面体单元辅助应用于人体表面平坦位置处,并重点考虑人体躯干网格构建,具体如图4所示。
人体模型各部位参照人体生理学结构区分人体骨骼和软组织并赋予相关材料属性。由于人体骨骼相比于人体肌肉组织不可压缩,因此,将人体骨骼设置为刚性,并参照文献[2223]将弹性模量赋值为16700 MPa,密度赋值为1700 kg/m3。人体肌肉组织密度确定为1060 kg/m3,并基于Mooney‑ Rivlin超弹性各向同性材料对人体肌肉部分进行建模,该模型可反映人‑椅系统动态交互过程中的非线性变形,定义如下:
W=A1(J1-3)+A2(J2-3)+A3(J3-2-1)+A4(J3-1)2
式中,W为应变能;J1J2J3为柯西‑格林公式中对应张量C的固定值,C定义为:
C=FTF
式中,F为变形梯度张量,张量C对应的三个固定值分别定义如下:
J1=trace(C)
J2=12[trace2(C)-trace(C2)]
J3=det(C)
上述公式中,材料参数A3A4与参数A1A2相关,定义如下:
A3=12A1+A2
A4=A1(5ν-2)+A2(11ν-5)2(1-2ν)
式中,ν为材料泊松比。结合文献[24-25]确定相关参数:A1=1.65 kPa,A2=3.35 kPa,ν=0.49。
本文基于试验研究,采用Solidworks软件构建块状开孔聚氨酯泡沫模型以表征实际测试座椅。在泡沫材料属性定义中,选用非线性各向同性可压缩超弹性材料,该材料的应力‑应变关系通过弹性应变函数G来表示,其计算公式如下:
G=i=1N2μiαi2{λ^1αi+λ^2αi+λ^3αi-3+limβi01βi[(Jel)-αiβi-1]}
式中,N为多项式阶数;μiαiβi为与温度相关的材料参数;λ^i=(Jth)-13λiλ^1λ^2λ^3=Jel,λi为主位移量;Jth为热应变(thermal-strain)体积变化比;Jel为弹性形变(elastic-deformation)体积变化比。结合最小二乘法确定以下参数:
μ1=164.861 kPa,α1=8.88413,β1=0.0,μ2=0.023017 kPa,α2=4.81798,β2=0.0
超弹性材料应力的主分量(柯西应力张量的主分量σ)可通过应变函数W相对于主位移量λi微分计算得到:
σi=(Jel)-1λiWλi
座椅泡沫材料的应力‑应变曲线如图5所示。
已建立的人体和座椅模型被赋予接触定义,组装为人‑椅系统有限元模型,为了图示清晰,网格已被隐藏(如图6所示)。人体的头‑胸部、胸‑上臂部、上臂‑下臂部、大腿‑臀部以及大腿‑小腿均设置为铰接触,即实现活动肢体围绕约束集中点转动但两者间无相对移动,各关节的刚度与阻尼定义如表1所示。人体与座椅之间、软组织与骨骼之间均采用“面对面”的接触方式进行,法向接触选用硬接触法,重力场大小设置为9.8 m/s2,方向为负轴。
在预测不同激励工况下的座椅频响函数之前,需对人‑椅系统有限元模型进行可靠性验证。图7所示为坐垫及靠背处静态体压分布图,坐垫区域的体压峰值主要集中于人体坐骨神经位置,呈典型的两点式分布。靠背区域的体压峰值分布主要位于两处肩胛骨接触位置和脊柱外突部分,呈现三点式分布。当人体在静态环境下接触挤压泡沫时,坐垫泡沫以及靠背泡沫均存在较为明显的压陷痕迹。坐垫处压陷痕迹与人体臀部形状相似,而靠背处的压陷痕迹则接近人体背部形状。模型预测得到的体压分布结果与试验测量及已有研究[26]较为吻合。
本文进一步采用垂向激励下坐垫处及靠背处频响函数实测数据校核模型,当模型受到垂向激励(0.4 m/s2)时,将坐垫处和靠背处的垂向同轴座椅频响函数仿真数据与测试数据进行对比,发现模型仿真结果与试验测得值拟合度较高,且变化趋势基本一致(如图8所示)。其中,对于坐垫处频响函数,模型预测得出的共振频率为4.78 Hz,共振处幅值为1.82,而试验测得值分别为4.75 Hz和1.92;对于靠背处座椅频响函数,模型预测的共振频率为4.86 Hz,共振处幅值为0.48,而试验测得值分别为4.91 Hz和0.49,本文建立的人‑椅系统有限元模型的座椅频响函数共振频率和共振处幅值响应预测值与实测数据基本吻合。
将上述校核完成后的人‑椅系统有限元模型应用于水平前后向激励工况下(激励幅值为0.4 m/s2)预测坐垫和靠背处水平前后向同轴频响函数。对比模型预测结果与试验测得值可知:模型预测得出的坐垫和靠背处水平前后向同轴频响函数与实测值变化趋势基本一致,但在共振频率处附近预测结果与试验数据拟合度较差(如图9所示)。
对于坐垫处同轴频响函数,模型预测得出的共振频率为2.78 Hz,共振处幅值为1.78,而试验测得值分别为2.75 Hz和1.32;对于靠背处同轴频响函数,模型预测得出的共振频率为4.25 Hz,共振处幅值为2.15,而试验测得值分别为4.75 Hz和1.98。综上,模型预测得出的坐垫处频响函数共振处幅值与实测值存在一定偏差,靠背处频响函数共振频率与试验测试值存在一定差异。
对比垂向和水平前后向激励下的人体振动模态发现,在垂向激励下,一阶振动模态主要由上肢的俯仰运动和肢体的垂向平移运动引起。而在水平前后向激励下,一阶振动模态则由臀部和大腿的水平前后向剪切运动以及上肢的俯仰运动引起(如图10所示)。在水平前后向激励条件下,坐垫与人体接触面之间的摩擦系数和阻尼参数对上述剪切运动具有显著影响。若摩擦系数设置过低,剪切运动可能被低估;反之则可能被高估。此外,剪切运动会引起座椅和人体接触面之间相对位移的变化,并产生附加运动。阻尼参数反映了接触面相对运动中由于内部耗能引起的能量损失程度。若阻尼参数设置过低,模型可能低估接触面上的振动能量耗散,导致剪切运动被过度放大。相反,若阻尼参数设置过高,模型可能高估能量耗散,导致剪切运动减弱。在垂向激励下进行模型校核时,由于上述参数对垂向振动响应预测精度的影响相对较小,未进行充分调校,因此在预测水平前后向激励下的座椅频响函数时可能会显著影响模型的预测精度。
同时,分析发现在水平前后向激励工况下,人体模型上半身围绕髋关节或腰椎关节的俯仰运动较为明显。在试验测试中,参试人员通过自主调节肌肉紧张程度和姿态控制来维持振动环境中的坐姿平衡,尤其是在共振频率处产生较大响应时,可能导致髋关节或腰椎关节的旋转刚度增加,并提高关节在振动中的稳定性,进而影响试验测得的靠背处水平前后向频响函数。然而,当前的有限元模型并未充分考虑这些生物反馈机能效应,导致模型预测的靠背处频响函数与试验测得值存在差异。因此,在将模型应用环境的输入激励由垂向调整为水平向时,有必要适度增加模型中髋关节或腰椎关节的旋转刚度参数,以弥补模型未能考虑到的生物反馈效应的不足,提高模型对水平前后向激励下靠背处频响函数的预测精度。未来的研究可以探索开发基于生物反馈的控制算法,模拟人体肌肉控制和姿态调整,并根据激励特征针对性地调整人体关节刚度参数或肌肉紧张度,以更准确地预测人‑椅系统在水平向振动下的传递特性。
随着垂向激励幅值从0.2增加至0.8 m/s2,模型预测得出的坐垫处垂向同轴频响函数共振频率及共振处幅值均呈降低趋势,靠背处垂向同轴频响函数表现出相似的非线性特性(如图11所示)。将模型预测结果与试验测得的中值数据进行对比发现:随垂向激励幅值增加,模型预测的坐垫处频响函数共振频率与共振处幅值变化趋势与试验测得值接近。在靠背处频响函数方面,模型预测的共振频率变化趋势与试验测得值接近,但在共振处幅值的变化趋势上存在一定差异。
当前的人‑椅系统有限元模型在不同垂向激励幅值条件下对坐垫及靠背处频响函数的共振特性进行了较为合理的预测。人体在不同振幅下呈现出的这种非线性“软化”特性主要受软组织刚度和阻尼在不同应变率和挤压程度下的显著差异的影响,这可能导致系统的振动特性呈现非线性变化,从而影响座椅频响函数的共振频率或共振处幅值。为了准确反映不同振动幅值下的系统响应特性,本文在定义人体软组织材料时采用了Mooney‑Rivlin模型。该模型基于应变能密度函数形式,能够适应不同振幅下的应变率和挤压程度。此外,在泡沫材料的定义中,本文引入了弹性应变函数,以更加真实地描述开孔聚氨酯泡沫材料特性,使得模型能够更准确地模拟泡沫坐垫在不同激励幅值下的变形,从而更好地预测人‑椅系统动力学响应特性。
随着水平前后向激励幅值从0.2增加至0.8 m/s2,模型预测得出的坐垫处频响函数共振频率及共振处幅值均呈下降趋势,靠背处频响函数表现出相似的非线性特性(如图12所示)。将模型预测结果与试验测得的中值数据进行对比,发现随水平前后向激励幅值增加,坐垫处频响函数共振频率变化趋势的预测结果与实验测得结果吻合度较高,但在共振频率处幅值方面,模型预测值与试验测得值仍存在一定偏差,在靠背处频响函数的预测中也呈现类似问题。
研究发现,尤其在水平前后向激励条件下,模型预测得出的座椅频响函数随激励幅值增加的变化趋势与试验测得值并不完全吻合。除人体与座椅聚氨酯泡沫材料参数的非线性影响外,人体与座椅的接触定义,尤其是摩擦系数和接触刚度,在座椅频响函数的非线性预测中较为关键。激励幅值的差异可能导致人‑椅接触面的形变或压缩程度发生变化,进而引起摩擦系数和接触刚度的动态变化。然而,这些接触参数在当前研究中被设定为固定值,可能影响了模型的预测精度。未来研究可进一步考虑接触参数的动态变化,以更准确地模拟人‑椅系统在不同激励幅值下的动态响应。此外,在定义人体软组织及泡沫材料时,虽已考虑材料的非线性应变,但材料属性定义中并未充分融合激励幅值的相关性,后续研究在构建人体软组织及泡沫材料模型时,应综合考虑材料属性定义与其激励特征的关联关系。同时,尽管试验测试与人‑椅系统模型设定的试验工况相同,但人体体征参数的差异性以及测试状态的随机性与不确定性也会影响模型预测精度。
本文以人‑椅系统的振动试验研究为基础,分别构建人体、座椅有限元简化模型,基于上述两个子系统模型结合体压分布数据对人‑椅界面接触参数进行校核,并利用垂向激励下的座椅频响函数试验结果校验模型,最终建立可同时预测垂向及水平前后向激励下坐垫及靠背处同轴座椅频响函数的人‑椅系统有限元模型。预测结果表明,坐垫及靠背处座椅频响函数共振频率预测值均随垂向及水平前后向激励幅值增加而降低,且变化趋势与试验测试结果基本一致。同时,座椅频响函数共振频率处幅值响应的预测值与实测数据仍存在一定误差,这可能是由参试人员体征参数的个体差异性所致。此外,将模型应用环境的输入激励由垂向调整为水平向时,需重点校核坐垫处接触参数及髋关节或腰椎关节的旋转刚度参数,以适应不同激励方向工况下的系统动态响应差异性。
  • 国家自然科学基金资助项目(51605010)
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doi: 10.16385/j.cnki.issn.1004-4523.202312005
  • 接收时间:2023-12-01
  • 首发时间:2026-02-04
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  • 收稿日期:2023-12-01
  • 修回日期:2024-01-15
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国家自然科学基金资助项目(51605010)
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    1.北京工业大学机械与能源工程学院,北京 100124;
    2.北京工业大学汽车结构部件先进制造技术教育部工程研究中心,北京 100124

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张筱璐(1984—),男,博士,副教授。E-mail:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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