关键词: 掘进参数, 地面沉降, 盾构隧道, 数据挖掘, 关联规则, Apriori算法

Abstract:

In order to effectively utilize the large amount of tunneling historical data, mining knowledge and information generated and accumulated in the process of shield tunneling to optimize tunneling parameters and control surface subsidence. The ground settlement data and tunneling parameters of adjacent sections of a metro are collected. Based on the data mining technology, the data are discretized by two methods: equal width discrete and kmeans clustering. By comparing advantages and disadvantages, and using Aprioir algorithm to mine association rules. Through the analysis of association rules, the following conclusions are obtained: The factors including excavated earth rate, grouting filling rate and pitching angle have a great impact on the settlement value. The tunneling speed and cutterhead torque also have a certain impact on the settlement value. According to the data discrete interval and association rules, the suggested grouting filling rate when tunneling through the soil with gravel and pebbles is 185%-190%, the suggested grouting pressure range is 0.16-0.22 MPa, and also suggested that pitching angle correction range on average every three ring is less than ±0.2°.

Key words: tunneling parameter, ground settlement, shield tunnel, data mining, association rules, Aprioir algorithm