煤矿行业作为全球经济的基础之一,面临着众多挑战,其中包括人力成本上升、工人安全和设备安全等问题。随着人工智能技术的快速发展,为煤矿行业提供了新的解决方案。研究旨在探索基于Transformer的多模态数据融合决策技术在煤矿单轨吊系统中的应用。通过融合视频数据和传感器数据,实现对单轨吊系统运行状态的全面监控,及时发现潜在风险,进行决策干预,减少事故发生,提升系统的安全性和运行效率。设计了基于Transformer的单轨吊多模态数据融合决策技术,实现了视觉信息与传感器数据的有效融合和信息共享。通过试验验证,融合传感器数据的模型在检测准确度和鲁棒性方面优于单独使用视觉信息的模型,为煤矿行业的智能化发展提供了新的思路和技术支持。

As one of the foundations of the global economy, the mining industry faces numerous challenges,including rising labor costs, worker safety, and equipment safety.With the rapid development of artificialintelligence technology, new solutions were provided for the mining industry. This study aims to explore theapplication of Transformer based multimodal data fusion decision-making technology in coal mine overhead monorailsuspension systems. By integrating video data and sensor data, comprehensive monitoring of the operational statusof the overhead monorail suspension system can be achieved, potential risks can be identified in a timely manner,decision-making interventions can be made, accidents can be reduced, and the safety and operational efficiency ofthe system can be improved. A Transformer based multimodal data fusion decision-making technology was designedfor overhead monorail, achieving effective fusion and information sharing of visual information and sensor data.Through experimental verification, the model that integrates sensor data had better detection accuracy androbustness than the model that uses visual information alone, providing new ideas and technical support for theintelligent development of the coal mining industry.