基于FP-growth算法的运行隧道结构安全关联分析

Bao Jiao, Hui Su, Xu Du, Bo Shi
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引用次数: 0

摘要

以某市6条地铁盾构隧道监测数据为基础,构建了包含35万个隧道段数据的标准化结构安全数据集。数据集中考虑了隧道管段变形、土体性质、埋深及周围环境等因素。采用FP-growth算法,对影响隧道结构安全的因素进行关联分析。针对隧道管段的结构缺陷,选取举升度作为评价管段收敛变形、运行年限和土体特性对管段缺陷影响的指标。基于隧道管段收敛变形的定量关联规则,分析了不同运营年限下独立因素对隧道管段收敛变形的影响。关联分析结果能反映管段病害和会聚变形的分布和发展规律,为地铁隧道的运行维护提供辅助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Structural Safety Association Analysis for Operating Tunnel based on FP-growth Algorithm
Based upon the monitoring data from shield tunnels of 6 subways in a city, the standardized structure safety data set containing 350,000 tunnel segment data is built. The tunnel segment deformation, soil property, buried depth and surrounding environment etc. are considered in the data set. With FP-growth algorithm, association analysis of the influence factors onto the tunnel structural safety is carried out. In view of the structural defects of tunnel segments, the lift degree is selected as the index to evaluate the influences of the convergent deformation of tunnel segments, operating years and soil characteristics on segment defects. Based on the quantitative association rules of convergent deformation of tunnel segments, the influence of the independent factor on the convergent deformation under different operating years is analyzed. The association analysis results can reflect the distribution and development law of segment disease and convergent deformation, which is assistive to the operation and maintenance of Metro tunnel.
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