基于图像识别技术的隧道工程监控管理系统设计

针对现有技术中隧道工程故障诊断存在的技术弊端,提出了一种利用巡检机器人进行智能化的监控管理方法,本研究通过巡检机器人对隧道工程的进度信息进行采集,通过图像识别技术实现隧道工程故障信息获取,通过多传感器数据信息融合模型对采集的信息进行处理,通过GIS技术对运维常的项目情况进行三维建模,并利用视觉点对三维建模中三角形空间单元进行删减,提高图像刷新率。通过模拟实验,本研究设计的巡检机器人监管方案的评价精度高,得出采用本研究设计的可视化监管方案可以使评价得分提升了21%。大大提高了隧道工程故障诊断能力。

Tunnel Engineering Fault Diagnosis Technology Based on Image Recognition Technology

Aiming at the technical drawbacks of tunnel engineering fault diagnosis in the existing technology, an intelligent monitoring and management method using inspection robots is proposed. Acquire the fault information of tunnel engineering, process the collected information through the multi-sensor data information fusion model, conduct 3D modeling of the normal operation and maintenance project through GIS technology, and use visual points to delete the triangular space units in the 3D modeling. , to increase the image refresh rate. Through simulation experiments, the inspection robot supervision scheme designed in this study has high evaluation accuracy, and it is concluded that the visual supervision scheme designed in this research can improve the evaluation score by 21%. It greatly improves the fault diagnosis ability of tunnel engineering.