摘要
为更加直观反映地下工程结构信息,充分发挥工程结构健康监测数据的价值,利用开源Cesium三维可视化引擎,构建地下空间结构三维可视化平台,通过实时接入、处理传感器收集到的监测数据,实现对隧道结构应变、沉降、倾斜的三维展示,开发植入基于循环神经网络的结构状态预测模型。结果表明,所开发的可视化平台能更加直观地反映地下工程结构信息,模型达到满意的预测精度。
In order to reflect the information of underground structure more directly and give full play to the value of health monitoring data of engineering structure,a three-dimensional(3D) visualization platform of underground space structure is constructed using open source Cesium 3D visualization engine.Through real-time access and processing of monitoring data collected by sensors,the three-dimensional display of strain,settlement and inclination of tunnel structure is realized,and a structural state prediction model based on cyclic neural network is developed.The results show that the developed visualization platform can reflect the information of underground engineering structure more directly,and the model achieves satisfactory prediction accuracy.
出处
《科技创新与应用》
2024年第7期51-54,共4页
Technology Innovation and Application
基金
南京工业大学大学生创新创业基金省级重点项目(202210291038Z)。
关键词
Cesium平台
工程可视化
地下工程
数据预测
预测模型
Cesium platform
engineering visualization
underground engineering
data prediction
prediction model
