当前位置: X-MOL 学术KSCE J. Civ. Eng. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Normative Visual Patterns for Hazard Recognition: A Crisp-Set Qualitative Comparative Analysis Approach
KSCE Journal of Civil Engineering ( IF 2.2 ) Pub Date : 2021-02-26 , DOI: 10.1007/s12205-021-1362-5
Heap-Yih Chong , Mingxuan Liang , Pin-Chao Liao

Understanding the mental representations used for hazard recognition would help the development of inspection strategies for effective safety management. This study is part of ongoing research to identify hazard recognition patterns based on users’ mental representations. Hence, this study explored normative visual patterns for improving hazard recognition performance using a crisp-set qualitative comparative analysis (cs-QCA). Eye-tracking data and visual trajectories were collected using an eye-tracking device in a structural laboratory. A cs-QCA approach was adopted to analyze and summarize normative visual patterns that were used to successfully detect hazards by all participants, namely, potential electrical contact, a large machine with no guardrails, and steel bars dump. The results show that object identification should suffice as the basis for identifying electricity-related hazards, while struck-by hazards should focus on the objects and their pivot points or potential movement trajectories. The experimental design and analytical approach provide new insights into visual analytics in hazard recognition. The research extends and supplements recognition by component theory in the context of construction hazard recognition. The results also provide new and practical references for hazard inspection training, as well as for future development of automated hazard recognition systems.



中文翻译:

危害识别的标准化视觉模式:一种脆集定性比较分析方法

了解用于危害识别的心理表征将有助于制定检查策略以进行有效的安全管理。这项研究是正在进行的研究的一部分,该研究旨在根据用户的心理表征来识别危害识别模式。因此,本研究使用清晰的定性比较分析(cs-QCA)探索了用于改善危害识别性能的规范视觉模式。在结构实验室中使用眼动仪收集眼动数据和视觉轨迹。采用了cs-QCA方法来分析和总结用于成功检测所有参与者危险的规范视觉模式,即潜在的电气接触,没有护栏的大型机器以及钢筋倾倒。结果表明,物体识别应足以作为识别与电力相关的危害的基础,而被击中的危害则应着重于物体及其枢轴点或潜在的运动轨迹。实验设计和分析方法为危害识别中的可视化分析提供了新的见解。该研究在构造危害识别的背景下扩展并补充了基于成分理论的识别。研究结果还为危害检查培训以及自动化危害识别系统的未来开发提供了新的实用参考。实验设计和分析方法为危险识别中的可视化分析提供了新的见解。该研究在构造危害识别的背景下扩展并补充了基于成分理论的识别。研究结果还为危害检查培训以及自动化危害识别系统的未来开发提供了新的实用参考。实验设计和分析方法为危险识别中的可视化分析提供了新的见解。该研究在构造危害识别的背景下扩展并补充了基于成分理论的识别。研究结果还为危害检查培训以及自动化危害识别系统的未来开发提供了新的实用参考。

更新日期:2021-04-13
down
wechat
bug