基于QN-MHP和Jack双模型验证的智能煤矿综合采矿系统接口的多目标优化研究
Xiaofang Yuan1,2, Xinxiang Zhang1,2, Hongzhi Yu1,2
1School of Management, Xi'an University of Science and Technology, People's Republic of China.
International journal of occupational safety and ergonomics : JOSE
|January 22, 2026
概括
这项研究优化了煤矿控制接口,以提高可用性和舒适性. 新的设计大大减少了操作人员的任务时间,错误和认知负载.
科学领域:
- 人与计算机的交互
- 人体工程学就是人体工程学.
- 工业系统工程 工业系统工程
背景情况:
- 智能煤矿系统需要用户友好的界面,以提高运营效率和安全.
- 当前的控制接口可能会在可用性和操作员舒适性方面带来挑战,影响性能.
研究的目的:
- 开发和验证一个多目标优化模型,以提高智能煤矿控制接口的可用性和操作舒适性.
- 改进操作员性能指标,如任务完成时间,错误率和认知负载.
主要方法:
- 开发了一个考虑层次结构,相关性,简单性,舒适性,可达性和可见性的多目标优化模型.
- 利用粒子群优化算法来解决模型.
- 使用杰克人体工程学模拟和QN-MHP认知建模方法验证了优化的界面.
主要成果:
- 优化界面导致任务完成时间减少了16.2%,错误率减少了75.0%.
- 视觉搜索时间减少了13.2%,认知负载减轻了.
- 观察到上肢舒适度和操作效率的提高.
结论:
- 多目标优化模型和多模式验证方法有效地增强了工业人机界面.
- 优化的界面设计在智能煤矿采矿环境中为操作人员的性能和舒适性提供了显著的改进.
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