基于分布式光纤的地铁隧道安全风险监测技术及其应用

Subway tunnel safety risk monitoring technology and application based on distributed optical fiber

全站机器人监测系统是地铁隧道安全风险监测的重要技术手段之一,但监测点相对有限。本文基于分布式光纤测量数据,提出了一种基于分布式光纤的地铁隧道安全风险监测技术。首先,将分布式光纤监测系统获取的应变数据映射为更加直观的变形位移数据;然后,通过确定3个输入参数、2个隐含层、1个输出参数,构建基于BP神经网络的应变-位移转换模型,验证结果表明,预测值和真实值的误差在0.2 mm以内,说明所建模型能较好地拟合数据的变化规律;最后,将其应用于青岛地铁1号线某区间,确定401.66~699.45με作为各测点预警值的安全区间,202.49~899.98με作为控制值的安全区间,计算结果与现场实测结果相吻合,误差满足工程需要。

The total station robot monitoring system is one of the important technical means of subway tunnel safety risk monitoring,but the monitoring points are relatively limited.Based on distributed optical fiber measurement data,the paper proposes a subway tunnel safety risk monitoring technology based on distributed optical fiber.Firstly,the strain data measured by distributed optical fiber monitoring system is mapped to more intuitive deformation and displacement data.Secondly,a strain-displacement transformation model based on BP neural network is constructed by determining 3 input parameters,2 hidden layers and 1 output parameter.The verification results show that the error between the predicted value and the real value is within 0.2 mm,indicating that the established model can better fit the change law of the data.Finally,it was applied to a certain section of Qingdao metro Line 1,and 401.66~699.45μεis determined as the safe interval of the early warning value of each measurement point,and 202.49~899.98μεis determined as the safe interval of the control value.The calculated results are consistent with the field measured results,and the errors meet the engineering needs.