变形监测是反馈工程安全最直接、最重要的手段之一,目前一般以人工监测为主,存在监测信息反馈慢、作业风险高等弊端,尤其是在工程遭遇有感地震、区域性暴雨等灾害时,实时采集数据、反馈监测信息和及时决策问题更为凸显。为此,以瀑布沟砾石土心墙堆石坝外部变形自动化监测工程为依托,对改正算法、监测方案、仪器野外保护、自动化控制和实时采集等展开了系列的研究与实践。提出了测量机器人基线边差分与气象融合改正测量法,以及TPS/GNSS融合互补监测方案,研发了一体化智能测站系统以及监测数据采集分析系统,具备采样频率自适应、观测时段自寻优、应急场景自识别、最优模型自匹配、精密仪器自防护功能,显著提高了变形监测数据质量,提升变形监测智能化水平,为行业变形自动化监测提供了一种可行的参考方案,具有一定推广应用价值。

Deformation monitoring is a most direct and important approach to feedback engineering safety, mainly manual monitoring at present. But manual monitoring features slow information feedback and high operational risk. Problems of real-time data collection, monitoring information feedback and timely decision-making are more prominent especially during earthquakes or regional rainstorms. In view of this, we proposed a method integrating baseline edge difference and meteorological fusion correction and the TPS/GNSS fusion complementary monitoring scheme by researching the correction algorithms, monitoring schemes, field protection of instruments, automatic control and real-time acquisition for the rockfill dam of the gravel earth core of Pubugou Project. Moreover, we developed an integrated intelligent monitoring station system and a monitoring data acquisition and analysis system. The system has functions of self-adapting sampling frequency, self-optimizing observation period, self-identifying emergency scene, self-matching optimal model, and self-protecting instrument. The system significantly improves the quality of deformation monitoring data, enhances the intelligence level of deformation monitoring, and provides a feasible reference solution for automatic deformation monitoring.