中国安全科学学报 ›› 2023, Vol. 33 ›› Issue (6): 122-127.doi: 10.16265/j.cnki.issn1003-3033.2023.06.2237

• 安全工程技术 • 上一篇    下一篇

起重吊装风险协同感知智能装备研发与应用

张淦(), 郭聖煜**(), 周晓洁, 董依梦, 吴迪, 肖天龙   

  1. 中国地质大学(武汉) 经济管理学院,湖北 武汉 430074
  • 收稿日期:2023-01-11 修回日期:2023-04-10 出版日期:2023-08-07
  • 通讯作者:
    **郭聖煜(1988—),男,湖北咸宁人,博士,副教授,主要从事工程安全和质量管理、风险管理等方面的研究。E-mail:
  • 作者简介:

    张淦 (1999—),男,山东枣庄人,硕士研究生,研究方向为工程安全管理。E-mail:

  • 基金资助:
    国家自然科学基金资助(71874165); 武汉市知识创新专项-曙光计划项目(2022010801020217); 国家级大学生创新创业训练计划(202210491003); 中央高校基本科研业务费交叉团队项目(CUG2642022006)

Research and application of intelligent device for collaborative perception of safety risk in lifting operations

ZHANG Gan(), GUO Shengyu**(), ZHOU Xiaojie, DONG Yimeng, WU Di, XIAO Tianlong   

  1. School of Economics and Management, China University of Geosciences, Wuhan Hubei 430074, China
  • Received:2023-01-11 Revised:2023-04-10 Published:2023-08-07

摘要:

为解决起重吊装指挥-操作交互的高风险场景下,单一类型装备(如传感器、智能摄像头等)难以实时智能地识别吊装风险的问题,研发集成计算机视觉技术和传感器设备的起重吊装风险协同感知智能装备(简称智能装备)。首先分析起重吊装过程中指挥人员和起重机的运动特征;然后针对起重机驾驶员的误操作行为风险,结合人-机不同的运动特征和工作需求,提出智能装备的风险协同感知方案;最后在实验室模拟场景下检验智能装备的风险感知精度和延迟时间。结果表明:智能装备能够协同感知起重吊装指挥-操作交互过程中的安全风险,发现起重机驾驶员的误操作行为并实时报警。智能装备在该过程中的风险感知精度为95.17%,延迟时间约为0.25 s。

关键词: 起重吊装, 风险感知, 协同感知, 智能装备, 轻量级混合卷积神经网络(MCN-Lite)

Abstract:

To address the limitations of single types of devices (e.g., sensors, intelligent cameras) in perceiving safety risks during the high-risk command-operation interactions in lifting operations, an intelligent device integrating computer vision technology and sensors (easily called an intelligent device) was developed for the collaborative perception of safety risks in lifting operations. First, the motion characteristics of the signalman and the crane in lifting were analyzed. Then, to eliminate the risk of crane operators' misoperation in lifting, a risk cooperative perception framework for the intelligent device was proposed in combination with the different motion characteristics and work requirements of man-machine. Finally, the feasibility test of the risk perception accuracy and risk perception latency of intelligent device was carried out in the laboratory simulation environment. The lab-based simulated experiment results demonstrate that the intelligent device could collaboratively perceive the safety risks during command-operation interaction in lifting operations. Instances of misoperation by crane operators can be alarmed in real-time, with a risk perception accuracy of 95.17% and a risk perception latency of approximately 0.25 s.

Key words: lifting operations, risk perception, collaborative perception, intelligent device, mixed convolutional neural network-lightweight (MCN-Lite)