视觉信息驱动的起重作业操作行为响应特性研究

晋良海, 王李成, 陈云, 吴志鹏 - 中国安全科学学报, 2022 - cssjj.com.cn
为了提高起重作业安全工效水平, 考虑可视角度与可视距离, 分析最佳视野可视锥与最大视野可
视锥, 并从几何光学角度测度起重作业视觉信息驱动水平; 以起重驾驶人作为被试 …

基于CNN 的3D 姿势估计在建筑工人行为分析中的应用

熊若鑫, 宋元斌, 王宇轩, 段彦娟 - 中国安全科学学报, 2019 - cssjj.com.cn
为实现建筑工人现场行为的自动化分析, 采用卷积神经网络(CNN) 检测3D 人体姿势并根据现场
条件对连续图像进行姿态估计; 考虑到动态和杂乱的施工现场环境(部分遮挡等) …

铁路工人人体行为识别模型

黄珍珍, 肖硕, 王钰, 陈伟, 王升志, 江海峰 - 中国安全科学学报, 2022 - cssjj.com.cn
为提高铁路工人施工安全系数, 采用基于人体行为识别(HAR) 的智能化监测方法,
估计铁路工人在施工过程中的动作; 使用端到端自动提取数据特征的深度学习方法搭建网络 …

受限空间钻孔工人的肌肉疲劳特性研究

徐胜, 金龙哲, 徐明伟 - 中国安全科学学报, 2019 - cssjj.com.cn
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 …

Human activity recognition model of railway workers

H Zhenzhen, X Shuo, W Yu, C Wei… - China Safety Science …, 2022 - cssjj.com.cn
In order to improve the construction safety factor of railway workers, the intelligent monitoring
method based on HAR was used to estimate the action of railway workers in the construction …

Application of convolutional neural network-based 3D posture estimation in behavioral analysis of construction workers

X Ruoxin, S Yuanbin, W Yuxuan… - China Safety Science …, 2019 - cssjj.com.cn
In order to facilitate an automated behavioral analysis of construction workers, CNN was
applied for 3D human pose estimation on sequential images. Considering the complicated …

Response characteristics of lifting operation driven by visual information

JIN Lianghai, W Licheng, C Yun… - China Safety Science …, 2022 - cssjj.com.cn
In order to improve safety of lifting operation, optimal visual field cone and maximum visual
field cone were analyzed considering visual angle and visual distance, and driving level of …

Study on muscle fatigue characteristics of drilled workers in confined space

XU Sheng, JIN Longzhe, XU Mingwei - China Safety Science Journal, 2019 - cssjj.com.cn
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 …