|本期目录/Table of Contents|

[1]周建亮,陈玮,范丽萍.基于生理指标的建筑工人攀登作业疲劳实验研究*[J].中国安全生产科学技术,2023,19(3):195-202.[doi:10.11731/j.issn.1673-193x.2023.03.029]
　ZHOU Jianliang,CHEN Wei,FAN Liping.Experimental study on climbing operation fatigue of construction workers based on physiological indexes[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2023,19(3):195-202.[doi:10.11731/j.issn.1673-193x.2023.03.029]
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基于生理指标的建筑工人攀登作业疲劳实验研究*
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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
19
期数:
2023年3期
页码:
195-202
栏目:
职业安全卫生管理与技术
出版日期:
2023-03-31

文章信息/Info

Title:
Experimental study on climbing operation fatigue of construction workers based on physiological indexes
文章编号:
1673-193X(2023)-03-0195-08
作者:
周建亮; 陈玮; 范丽萍
（中国矿业大学 力学与土木工程学院，江苏 徐州 221116）
Author(s):
ZHOU Jianliang;  CHEN Wei;  FAN Liping
(School of Mechanics and Civil Engineering,China University of Mining and Technology,Xuzhou Jiangsu 221116,China)
关键词:
建筑工人; 生理指标; 疲劳检验; 攀登作业; 支持向量机
Keywords:
construction worker;  physiological index;  fatigue test;  climbing operation;  support vector machine
分类号:
X947；TU741
DOI:
10.11731/j.issn.1673-193x.2023.03.029
文献标志码:
A
摘要:
为研究攀登作业建筑工人生理疲劳状态的评测指标，提出1种基于生理指标的建筑工人攀登作业疲劳测度实验方法。首先，设计实验测量建筑工人的心率、皮肤温度、舒张压、收缩压4项生理指标，结合Brog’s RPE主观疲劳程度量表研究建筑工人生理疲劳的变化；其次，提取上述4项指标的平均值和标准差作为生理指标特征值，利用静息状态下生理指标特征值和疲劳状态下生理指标特征值进行方差分析、球形检验、T检验筛选出与疲劳相关的特征值；最后，利用支持向量机构建疲劳检测模型。研究结果表明：上述8项生理指标特征值与攀登作业工人疲劳具有显著相关性，疲劳检测模型的准确率为96.875%，研究结果可对攀登作业人员疲劳评估和疲劳预警具有实践性意义。
Abstract:
In order to study the evaluation indexes of physiological fatigue state of construction workers in climbing operation,an experimental method for measuring the fatigue state of construction workers in climbing operation based on the physiological indexes was proposed.First,the experiments were designed to measure the four physiological indexes of construction workers,including the heart rate,skin temperature,diastolic blood pressure and systolic blood pressure,and combined with Brog’s RPE subjective fatigue scale,the change in the physiological fatigue of construction workers was studied.Secondly,the average values and standard deviation of the above four indexes were extracted as the eigenvalues of the physiological indexes,and the eigenvalues of the physiological indexes in the resting state and the eigenvalues of the physiological indexes in the fatigue state were used to carry out the analysis of variance,spherical test,and T test,so as to screen out the eigenvalues related to fatigue.Finally,the support vector machine was used to build a fatigue detection model.The research results showed that the eigenvalues of the above eight physiological indexes were significantly correlated with the fatigue of workers in climbing operation,and the accuracy of the fatigue detection model was 96.875%.The results can provide practical significance for the fatigue assessment and fatigue warning of workers in climbing operation.

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备注/Memo

备注/Memo:
收稿日期： 2022-03-24
* 基金项目： 国家自然科学基金项目（72171224）;教育部人文社科规划基金项目（19YJAZH122）;江苏省研究生实践创新计划项目（SJCX21_1066）;中国矿业大学国家级大学生创新训练计划项目（201910290090Z）
作者简介： 周建亮，博士，教授，主要研究方向为BIM与VR技术、智慧建造与工程建设安全管理。
通信作者： 陈玮，硕士研究生，主要研究方向为行为安全管理。
更新日期/Last Update: 2023-04-12