地铁深基坑变形数据的挖掘分析与风险识别

Deformation data-mining and risk identification of subway deep excavation

基坑工程的隐患发展成工程事故之前兆,必定表现在监测数据某些特征的异常变化,此时若据此及时采取相应的措施,便能够以很小的代价避免或降低工程风险。以地铁基坑工程的大量监测数据为基础,通过数据挖掘方法寻找工程风险和变形数据特征变化值之间的内在联系和相关规律,以形成量化的评判指标来识别和评价工程的危险程度,从数据分析的角度提供了一种发现和控制工程风险的办法。

The omen of engineering accidents is inevitably reflected in the abnormal response of monitoring data. The measures adopted in time before accidents may minimize or avoid the engineering risks. Based on the large amount of data collected from metro projects of deep excavation, the correlation between risks and deformation data was discovered and the quantity indexes of risk identification were found to be defined by data mining technology. It is a valuable and reliable method to predict and control risks.