片岩隧道变形规律分析与预测方法研究  

Study on deformation law analysis and prediction method of schist tunnel

作　　者：刘盛辉[1] 王娟[1] 李常茂[1] 祝和意[1] LIU Shenghui;WANG Juan;LI Changmao;ZHU Heyi(Shaanxi Railway Institute,Weinan Shaanxi 714000,China)

机构地区：[1]陕西铁路工程职业技术学院,陕西渭南714000

出　　处：《中国安全生产科学技术》2022年第2期184-190,共7页Journal of Safety Science and Technology

基　　金：渭南市科技计划项目(2021ZDYF-JCYJ-265);陕西铁路工程职业技术学院2020年科研基金项目(KY2020-28);陕西铁路工程职业技术学院建筑施工技术科技创新团队基金项目(KJTD201804)。

摘　　要：为准确掌握片岩隧道变形规律,基于隧道变形监测结果,利用核极限学习机构建隧道变形初步预测模型,通过遗传算法和蚁群算法进行优化处理,以保证模型参数的最优性,采用混沌理论对预测误差进行修正处理,利用M-K分析判断隧道变形趋势,并将趋势判断结果与预测结果对比。结果表明:通过递进优化处理,能逐步提高预测精度,且预测结果的相对误差均值介于1.77%~1.83%,均小于2%,具有较高的预测精度;隧道变形虽呈增加趋势,但随时间增长其增长趋势逐渐减弱,总体趋于稳定方向发展。In order to accurately grasp the deformation law of schist tunnel,based on the results of tunnel deformation monitoring,the kernel limit learning machine was used to build a preliminary prediction model of tunnel deformation,and the optimization processing of genetic algorithm and ant colony algorithm were used to ensure the optimality of parameters in the model.The chaos theory was used to correct the prediction error,then the M-K analysis was used to judge the trend of tunnel deformation,and the trend judgment results were compared with the prediction results,so as to realize the comprehensive study of tunnel deformation law.The results showed that the prediction accuracy could be improved step by step through the progressive optimization processing,and the average relative error of the prediction results was between 1.77%~1.83%,which were all less than 2%,so the prediction accuracy was higher.At the same time,by judging the deformation trend,it was found that although the tunnel deformation had an increasing trend,the trend continued to weaken with time.Therefore,the tunnel deformation presented an increasing trend with small rate and tended to be stable generally.

关 键 词：交通运输安全 隧道 变形预测 混沌理论 趋势判断 变形规律 

分 类 号：X947[环境科学与工程—安全科学]