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人工神经网络用于人体振动响应的分析
引用本文:戴诗亮,沈成武,沈延春,汪芳子.人工神经网络用于人体振动响应的分析[J].清华大学学报(自然科学版),1996(8).
作者姓名:戴诗亮  沈成武  沈延春  汪芳子
作者单位:清华大学工程力学系,武汉交通科技大学建工系,武汉职工医学院,航天医学工程研究所
基金项目:国家教委开放实验室基金
摘    要:要对振动环境中的人体进行保护,必须研究人体振动特性。人体全身振动共振频率是一个很重要的动力学参数。对不同身高h、体重w及不同振级a下坐姿人体全身振动的第1阶共振频率f进行了测量,获得了39组数据。利用三层人工神经网络对这些数据进行了分析,排除了个体差异,寻找出h,w及a与f的普遍映射关系,从而可以根据h,w及a预测呈非线性关系的f值,对人机工程学设计及相关研究有重要意义。

关 键 词:人工神经网络,人体振动,共振频率

Analysis of the human vibration response by artificial neural networks
Dai Shiliang, Shen Chengwu, Shen Yanchun, Wang Fangzi.Analysis of the human vibration response by artificial neural networks[J].Journal of Tsinghua University(Science and Technology),1996(8).
Authors:Dai Shiliang  Shen Chengwu  Shen Yanchun  Wang Fangzi
Abstract:Dynamic characters of human body must be researched for human vibration protection. The resonant frequency of whole human body is a very important dynamic parameter. The data of 39 groups were measured from human iliocristale during whole body vibration in sitting position. Using three-level arificial neural network, the relation between human vibration resonant frequency and height, weight of human body, vibration level was analysed. The common reflective relation of the resonant frequency to the height, weight of the body and exciting acceleration was obtained by eliminating the individual differences.Based on the height, weight of body arid vibration level the resonant frequency could be predicted. This study is important to the ergonomical design and relevant study.
Keywords:artificial neural network  human body vibration  resonant frequency
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