中国安全科学学报 ›› 2019, Vol. 29 ›› Issue (3): 76-81.doi: 10.16265/j.cnki.issn1003-3033.2019.03.013

• 安全工程技术科学 • 上一篇    下一篇

受限空间钻孔工人的肌肉疲劳特性研究

徐胜, 金龙哲 教授, 徐明伟   

  1. 北京科技大学 土木与资源工程学院,北京 100083
  • 收稿日期:2018-12-12 修回日期:2019-02-19 发布日期:2020-11-26
  • 作者简介:徐 胜 (1996—),男,安徽淮南人,硕士研究生,研究方向为安全人机工程、输油管道泄漏风险评价等。E-mail:xsgz0124@163.com。
  • 基金资助:
    “十三五”国家重点研发计划(2016YFC0801706)。

Study on muscle fatigue characteristics of drilled workers in confined space

XU Sheng, JIN Longzhe, XU Mingwei   

  1. School of Civil and Resource Engineering, University of Science & Technology Beijing, Beijing 100083, China
  • Received:2018-12-12 Revised:2019-02-19 Published:2020-11-26

摘要: 为了研究受限空间下钻孔工人在作业过程中的肌肉疲劳特征,通过模拟试验,测量立姿、半蹲姿、全蹲姿姿势下,颈夹肌、胸腰筋膜等10块肌肉的表面肌电值(sEMG);用中值频率(MF)作为指标,根据MF下降率评定各肌肉的疲劳程度,并通过设置不同的时间梯度,对比疲劳程度的变化,从而提出减轻肌肉疲劳的方案。试验结果表明:肌肉疲劳程度越深,MF下降越快;腰部3种姿势下均表现出较高的下降率(0.374±0.129),立姿中颈部下降率(0.60)、蹲姿中小腿胫骨肌下降率(0.55)也较高;而调整作业周期可以使MF值下降1.33~9.85倍,有效减轻疲劳程度。

关键词: 受限空间, 作业姿势, 肌肉疲劳, 表面肌电(sEMG), 中值频率(MF)

Abstract: In order to study the muscle fatigue characteristics of drilling workers in confined spaces, the sEMG of ten muscles such as splenius cervicis and thoracolumbar fascia was measured under standing posture, semi-squatting posture and full knee posture through the simulation experiments. Using the MF as an indicator, the fatigue degree of each muscle was evaluated according to the MF reduction rate, and different time gradients were set to compare the change of fatigue degree, thereby proposing a solution to reduce muscle fatigue. The experimental results show that the deeper the muscle fatigue degree is, the faster the MF declines, that the waist shows a high rate of decline (0.374±0.129) in all three postures, that the drop rate (0.60) of the neck is higher in the standing position and the drop rate (0.55) of tibial muscle is higher in the kneeling position, and that the adjustment of the working cycle can reduce the MF value by 1.33-9.85 times and effectively reduce fatigue.

Key words: confined space, homework posture, muscle fatigue, surface electromyography(sEMG), median frequency(MF)

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