摘要
针对现有监测预警方法对建筑结构变形监测预警时,存在结果残差过大,影响精度的问题,引入改进人工神经网络,开展对建筑结构变形智能监测方法的设计研究。利用改进人工神经网络,构建建筑结构变形预测模型;在各结构变形监测点设置传感器,实现建筑结构变形数据实时监测;设置报警阈值,结合模型输出结果与阈值的对比,实现对建筑结构变形智能预警。通过对比实验证明,新方法的监测预警结果残差得到有效控制,精度显著提升,能够在第一时间发现建筑结构异常变形趋势,促进提高建筑整体建设的安全性。
In view of the existing monitoring and early warning methods for building structure deformation monitoring and early warning,the residual error of the result is too large,which affects the accuracy of the problem,improved artificial neural network is introduced to carry out the design and research of intelligent monitoring method for building structure deformation.The deformation prediction model of building structure is constructed by using improved artificial neural network.Sensors are set up at each monitoring point to realize real-time monitoring of structural deformation data.The alarm threshold is set,and the intelligent early warning of building structure deformation is realized by comparing the model output result with the threshold value.Through comparative experiments,it is proved that the new method can effectively control the residual error of monitoring and warning results,and the accuracy is significantly improved.It can detect abnormal deformation trends of building structures in the first time,promoting the improvement of the overall safety of building construction.
作者
景立飞
JING Lifei(Chifeng Luda Municipal Engineering Co.,Ltd.,Chifeng,Inner Mongolia 024000,China)
出处
《自动化应用》
2024年第5期182-184,共3页
Automation Application
关键词
改进人工神经网络
智能监测
建筑结构
improved artificial neural network
intelligent monitoring
building structure
